• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Korean Medicine Rehabilitation
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• v.18 no.4
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• pp.39-61
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• 2008

Objectives : The present study was performed to investigate whether acupuncture stimulation in the rats affected regeneration properties of the injured sciatic nerve. A differential effect of acupuncture stimulation on the one point near the spinal nerve root controlling sciatic nerve activity and the other point in the peripheral area subordinated by injured nerve was compared. Materials and Methods: Rat sciatic nerves were injured by crush, and the effects on axonal regeneration on injured sciatic nerves were evaluated by acupuncture stimulation at two different regions. In proximal acupuncture stimulation group, acupuncture stimulation was performed on Huatuo Jiaji(EX B2) points located from L5 to S1 vertebral levels to stimulate the nearest spinal nerve root that innervates sciatic nerves. In distal acupuncture stimulation group, acupuncture stimulation was performed on Zusanli(ST 36) and Weizhong(BL 40) points to stimulate at peripheral area dominated by injured sciatic nerves. Acupuncture stimulation was given every other days for 1 or 2 weeks. Sciatic nerve tissues collected from acupuncture stimulation experimental groups, injury control group, and intact animal group were used for protein analysis by Western blotting or Hoechst nuclear staining. To determine axonal regeneration, Dil fluorescence dye was injected into the sciatic nerve 0.5 cm distal to the injury site in individual animal groups and Dil-labeled cells by retrograde tracing were measured in the DRG at lumbar 5 or in the spinal cord. DRG sensory neurons prepared from individual animal groups were used to measure the extent of neurite outgrowth and for immunofluorescence staining with anti-GAP-43 antibody. Results : Animal groups given proximal or distal acupuncture stimulation showed upregulation of GAP-43 and Cdc2 protein levels in the sciatic nerve at 7 days after injury. Cdk2 protein levels were strongly induced by nerve injury, but did not show changes by acupuncture stimulation. Phospho-Erk1/2 protein levels were elevated by acupuncture stimulation above those present in the injury control animals. These increase in regeneration-associated protein levels appeared to be related with increase cell proliferation in the injured sciatic nerves. Hoechst 33258 staining of sciatic nerve tissue to visualize nuclei of individual cells showed increased Schwann cell number in the distal portion of the injured nerve 7 and 14 days after injury and further increases by acupuncture stimulation particularly at the proximal position. Measurement of axonal regeneration by retrograde tracing showed significantly increased Dil-labeled cells in proximal acupuncture stimulation group compared to distal acupuncture stimulation group and injury control group. Finally, an evaluation of axonal regeneration by retrograde tracing showed increased number of Dil labeled cells in the DRG at lumbar 5 or in the ventral horn of the spinal cord at lower thoracic level at 7 days after nerve injury. Conclusions : The present data show that the proximal acupuncture stimulation at Huatuo Jiaji(EX B2) points governing injured sciatic nerves was more effective for axonal regeneration than the distal acupuncture stimulation. Further studies on functional recovery or associated molecular mechanisms should be critical for developing animal models and clinical applications.

• Journal of Korean Society of Forest Science
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• v.38 no.1
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• pp.33-45
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• 1978

The purpose of present study is to analyze the genetic variation of natural stand of Pinus densiflora. In 1975 following after the selection of 1974, twenty trees from each of three natural populations of the species were selected and their open-pollinated seeds were collected, and the locations and conditions of the populations ate presented in table 1, 2 and figure 1. Some morphological traits of the populations were already detailed in our second report of this series, in which Myong-Ju and Ul-Jin populations were regarded to be superior phenotypically to suweon population. The morphological traits of cone, seed and seed-wing, and also the growth performances and needle characters of the seedling were observed in the present study according to the previous methods. The results obtained are summarized as follows; 1. The meteorological data obtained by averaging the records of 30 year period (1931~1960) measured from the nearest meteorological stations to each population are shown in fig.2, 3, 4. The distributional patterns of investigated climate factors are generally considered to be similar among the locations. However, the precipitation density during growing season and the air temperature during dormant season on Suweon area, population 6, were quite different from those of the other areas. 2. The measurements of fresh cone weight, length, diameter and cone index, i.e., length to diameter ratio are presented in table 7. As shown in table 7, all these traits except for cone diameter seem to be highly significant in population differences and family differences within population. 3. The morphological traits of seed and seed-wing are detailed in table 8, 9, and highly significant differences are recognized among the populations and the families within population in seed-wing length, seed-wing index, seed weight, seed-length and seed index but not among the populations in the other observed traits. The values of correlation coefficient between the characters of cone and seed are given in table 10 and the positive significant correlations can be observed in the most parts of the compared traits. 4. Significant statistical differences among populations and families within population are observed in the growth performances of 1-0 and 1-1 seedling height of these progenies. But the differences in root collar diameter are shown only among families within population. As shown in table 13, the most parts of correlations are not significant statistically between the growth performances of seedling and the seed characters. 5. The number of stomata row on both sides of needle and the serration density were measured in the seedlings from each of the families of the three populations. As shown in table 15, statistical differences are considered to be significant among the populations and among the families within population in serration density but not among the populations in stomata row on both sides of the needle. The results differ from those of the third report of this series. Even if one of the reason seems to be the diversity of selected populations, it could not be confirmed definitely. The correlations between progenies and parents are not generally observed in the investigated traits of needle as shown in table 16.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Korean Society of Forest Science
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• v.43 no.1
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• pp.20-30
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• 1979

The purpose of present study is to analyze the genetic variation of natural stand of Pinus densiflora. In 1976 following after the seletion of 1974 and 1975, twenty trees from each of three natural populations of the species were selected and seeds were collected, and the locations and conditions of populations are presented in table 1, 2 and figure 1. Some morphological traits of the populations were already detailed in our fifth report of this series. The morphological traits of cone, seed and seed-wing, and also the growth performances and needle characters of the seedling were observed in the present study according to the previous methods. The results obtained are summarized as follows; 1. The meteorological data obtained by averaging the records of 30 year period(1931~1960) measured from the nearest meteorological station to each population are shown in fig. 2, 3, 4. The distributional patterns of investigated climate factors are generally considered to be similar among the locations. However, the precipitation density during growing season and the air temperature during dormant season on Samchuk area (Pop. 9) were quite different from those of the other areas. 2. The measurements of fresh cone weight, length, diameter and cone index (i.e.: length to diameter ratio) are presented in table 7. As shown in table 7, all these traits except for cone diameter seem to be not significant in population and to be highly significant in family differences within population. 3. The morohological traits of seed and seed-wing are detailed in table 8, 9, and highly significant differences are recognized among the populations and the families within population in seed weight, seed length, seed thickness but not among the populations in the other observed traits. The values of correlation between the characteristics of cone and seed are presented in table 12. As shown, the correlation between cone length and seed wing length, between seed wing width and seed width were significantly positive in population 8 and 9 but in population 7. The positive correlations between seed length and seed width were calculated in all populations studied 4. Significant statistical differences among populations and families within population are observed in the growth performances of 1-0 seedling height of these progenies. But the differences in 1-1 seedling height and root collar diameter are shown only among familes within population. As shown in table 13, the most parts of correlations are not significant statistically between the growth performances of seedling and the seed characters. 5. As shown in table 15, statistical differences are considered to be significant among the populations in stomata row on both sides of the needle but not in serration density. The correlations between progenies and parents are not generally observed in the investigated traits of needle as shown in table 16.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.3-4
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• 2004

Results will be presented from two field studies that evaluated the in-situ treatment of chlorinated aliphatic hydrocarbons (CAHs) using aerobic cometabolism. In the first study, a cometabolic air sparging (CAS) demonstration was conducted at McClellan Air Force Base (AFB), California, to treat chlorinated aliphatic hydrocarbons (CAHs) in groundwater using propane as the cometabolic substrate. A propane-biostimulated zone was sparged with a propane/air mixture and a control zone was sparged with air alone. Propane-utilizers were effectively stimulated in the saturated zone with repeated intermediate sparging of propane and air. Propane delivery, however, was not uniform, with propane mainly observed in down-gradient observation wells. Trichloroethene (TCE), cis-1, 2-dichloroethene (c-DCE), and dissolved oxygen (DO) concentration levels decreased in proportion with propane usage, with c-DCE decreasing more rapidly than TCE. The more rapid removal of c-DCE indicated biotransformation and not just physical removal by stripping. Propane utilization rates and rates of CAH removal slowed after three to four months of repeated propane additions, which coincided with tile depletion of nitrogen (as nitrate). Ammonia was then added to the propane/air mixture as a nitrogen source. After a six-month period between propane additions, rapid propane-utilization was observed. Nitrate was present due to groundwater flow into the treatment zone and/or by the oxidation of tile previously injected ammonia. In the propane-stimulated zone, c-DCE concentrations decreased below tile detection limit (1 $\mu$g/L), and TCE concentrations ranged from less than 5 $\mu$g/L to 30 $\mu$g/L, representing removals of 90 to 97%. In the air sparged control zone, TCE was removed at only two monitoring locations nearest the sparge-well, to concentrations of 15 $\mu$g/L and 60 $\mu$g/L. The responses indicate that stripping as well as biological treatment were responsible for the removal of contaminants in the biostimulated zone, with biostimulation enhancing removals to lower contaminant levels. As part of that study bacterial population shifts that occurred in the groundwater during CAS and air sparging control were evaluated by length heterogeneity polymerase chain reaction (LH-PCR) fragment analysis. The results showed that an organism(5) that had a fragment size of 385 base pairs (385 bp) was positively correlated with propane removal rates. The 385 bp fragment consisted of up to 83% of the total fragments in the analysis when propane removal rates peaked. A 16S rRNA clone library made from the bacteria sampled in propane sparged groundwater included clones of a TM7 division bacterium that had a 385bp LH-PCR fragment; no other bacterial species with this fragment size were detected. Both propane removal rates and the 385bp LH-PCR fragment decreased as nitrate levels in the groundwater decreased. In the second study the potential for bioaugmentation of a butane culture was evaluated in a series of field tests conducted at the Moffett Field Air Station in California. A butane-utilizing mixed culture that was effective in transforming 1, 1-dichloroethene (1, 1-DCE), 1, 1, 1-trichloroethane (1, 1, 1-TCA), and 1, 1-dichloroethane (1, 1-DCA) was added to the saturated zone at the test site. This mixture of contaminants was evaluated since they are often present as together as the result of 1, 1, 1-TCA contamination and the abiotic and biotic transformation of 1, 1, 1-TCA to 1, 1-DCE and 1, 1-DCA. Model simulations were performed prior to the initiation of the field study. The simulations were performed with a transport code that included processes for in-situ cometabolism, including microbial growth and decay, substrate and oxygen utilization, and the cometabolism of dual contaminants (1, 1-DCE and 1, 1, 1-TCA). Based on the results of detailed kinetic studies with the culture, cometabolic transformation kinetics were incorporated that butane mixed-inhibition on 1, 1-DCE and 1, 1, 1-TCA transformation, and competitive inhibition of 1, 1-DCE and 1, 1, 1-TCA on butane utilization. A transformation capacity term was also included in the model formation that results in cell loss due to contaminant transformation. Parameters for the model simulations were determined independently in kinetic studies with the butane-utilizing culture and through batch microcosm tests with groundwater and aquifer solids from the field test zone with the butane-utilizing culture added. In microcosm tests, the model simulated well the repetitive utilization of butane and cometabolism of 1.1, 1-TCA and 1, 1-DCE, as well as the transformation of 1, 1-DCE as it was repeatedly transformed at increased aqueous concentrations. Model simulations were then performed under the transport conditions of the field test to explore the effects of the bioaugmentation dose and the response of the system to tile biostimulation with alternating pulses of dissolved butane and oxygen in the presence of 1, 1-DCE (50 $\mu$g/L) and 1, 1, 1-TCA (250 $\mu$g/L). A uniform aquifer bioaugmentation dose of 0.5 mg/L of cells resulted in complete utilization of the butane 2-meters downgradient of the injection well within 200-hrs of bioaugmentation and butane addition. 1, 1-DCE was much more rapidly transformed than 1, 1, 1-TCA, and efficient 1, 1, 1-TCA removal occurred only after 1, 1-DCE and butane were decreased in concentration. The simulations demonstrated the strong inhibition of both 1, 1-DCE and butane on 1, 1, 1-TCA transformation, and the more rapid 1, 1-DCE transformation kinetics. Results of tile field demonstration indicated that bioaugmentation was successfully implemented; however it was difficult to maintain effective treatment for long periods of time (50 days or more). The demonstration showed that the bioaugmented experimental leg effectively transformed 1, 1-DCE and 1, 1-DCA, and was somewhat effective in transforming 1, 1, 1-TCA. The indigenous experimental leg treated in the same way as the bioaugmented leg was much less effective in treating the contaminant mixture. The best operating performance was achieved in the bioaugmented leg with about over 90%, 80%, 60 % removal for 1, 1-DCE, 1, 1-DCA, and 1, 1, 1-TCA, respectively. Molecular methods were used to track and enumerate the bioaugmented culture in the test zone. Real Time PCR analysis was used to on enumerate the bioaugmented culture. The results show higher numbers of the bioaugmented microorganisms were present in the treatment zone groundwater when the contaminants were being effective transformed. A decrease in these numbers was associated with a reduction in treatment performance. The results of the field tests indicated that although bioaugmentation can be successfully implemented, competition for the growth substrate (butane) by the indigenous microorganisms likely lead to the decrease in long-term performance.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Korean Society of Forest Science
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• v.32 no.1
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• pp.36-63
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• 1976

The purpose of this study is to elucidate the genetic variation of the natural forest of Pinus densiflora. Three natural populations of the species, which are considered to be superior quality phenotypically, were selected. The locations and conditions of the populations are shown in table 1 and 2. The morphological traits of tree and needle and some other characteristics were presented already in our first report of this series in which population and family differences according to observed characteristics were statistically analyzed. Twenty trees were sampled from each populations, i.e., 60 trees in total. During the autumn of 1974, matured cones were collected from each tree and open-pollinated seeds were extracted in laboratory. Immediately after cone collection, in closed condition, the morphological characteristics were measured. Seed and seed-wing dimensions were also studied. In the spring of 1975, the seeds were sown in the experimental tree nursery located in Suweon. And in the April of 1976, the 1-0 seedlings were transplanted according to the predetermined experimental design, randomized block design with three replications. Because of cone setting condition. the number of family from which progenies were raised by populations were not equal. The numbers of family were 20 in population 1. 18 in population 2 and 15 in population 3. Then, each randomized block contained seedlings of 53 families from 3 populations. The present paper is mainly concerned with the variation of some characteristics of cone, seed, needle, growth performance of seedlings, and chlorophyll and monoterpene compositions of needles. The results obtained are summerized as follows. 1. The meteorological data obtained by averaging the records of 30 year period, observed from the nearest station to each location of populations, are shown in Fig. 3, 4, and 5. The distributional pattern of monthly precipitation are quite similar among locations. However, the precipitation density on population 2, Seosan area, during growing season is lower as compared to the other two populations. Population 1. Cheong-song area, and population 3, Pyong-chang area, are located in inland, but population 2 in the western seacoast. The differences on the average monthly air temperatures and the average monthly lowest temperatures among populations can hardly be found. 2. Available information on the each mother trees (families) studied, such as age, stem height, diameter at breast height, clear-bole-length, crown conditions and others are shown in table 6,7, and 8. 3. The measurements of fresh cone weight, length and the widest diameter of cone are given in Tab]e 9. All these traits arc concerned with the highly significant population differences and family differences within population. And the population difference was also found in the cone-index, that is, length-diameter ratio. 4. Seed-wing length and seed-wing width showed the population differences, and the family differences were also found in both characteristics. Not discussed in this paper, however, seed-wing colours and their shapes indicate the specificity which is inherent to individual trees as shown in photo 3 on page 50. The colour and shape are fully the expression of genetic make up of mother tree. The little variations on these traits are resulted from this reason. The significant differences among populations and among families were found in those characteristics, such as 1000-seed weight, seed length, seed width, and seed thickness as shown in table 11. As to all these dimensions, the values arc always larger in population 1 which is younger in age than that of the other two. The population differences evaluated by cone, seed and seed-wing sizes could partly be attributed to the growth vigorousity. 5. The values of correlation between the characteristics of cone and seed are presented in table 12. As shown, the positive correlations between cone diameter and seed-wing width were calculated in all populations studied. The correlation between seed-wing length and seed length was significantly positive in population 1 and 3 but not in population 2, that is, the r-value is so small as 0.002. in the latter. The correlation between cone length and seed-wing length was highly significant in population 1, but not in population 2. 6. Differences among progenies in growth performances, such as 1-0 and 1-1 seedling height and root collar diameter were highly singificant among populations as well as families within population(Table 13.) 7. The heritability values in narrow sense of population characteristics were estimated on the basis of variance components. The values based on seedling height at each age stage of 1-1 and 1-0 ranged from 0.146 to 0.288 and the values of root collar diameter from 0.060 to 0.130. (Table 14). These heritability values varied according to characteristics and seedling ages. Here what must be stated is that, for calculation of heritability values, the variance values of population was divided by the variance value of environment (error) and family and population. The present authors want to add the heritability values based on family level in the coming report. It might be considered that if the tree age is increased in furture, the heritability value is supposed to be altered or lowered. Examining the heritability values studied previously by many authors, in pine group at age of 7 to 15, the values of height growth ranged from 0.2 to 0.4 in general. The values we obtained are further below than these. 8. The correlation between seedling growth and seed characteristics were examined and the values resulted are shown in table 16. Contrary to our hypothetical premise of positive correlation between 1-0 seedling height and seed weight, non-significance on it was found. However, 1-0 seedling height correlated positively with seed length. And significant correlations between 1-0 and 1-1 seedling height are calculated. 9. The numbers of stomata row calculated separately by abaxial and adaxial side showed highly significant differences among populations, but not in serration density. On serration density, the differences among families within population were highly significant. (Table 17) A fact must be noted is that the correlation between stomata row on abaxial side and adaxial side was highly significant in all populations. Non-significances of correlation coefficient between progenies and parents regarding to stomata row on abaxial side were shown in all populations studied.(Table 18). 10. The contents of chhlorophyll b of the needle were a little more than that of chlorophyll a irrespective of the populations examined. The differences of chlorophyll a, b and a plus b contents were highly significant but not among families within populations as shown in table 20. The contents of chlorophyll a and b are presented by individual trees of each populations in table 21. 11. The occurrence of monoterpene components was examined by gas liquid chromatography (Shimazu, GC-1C type) to evaluate the population difference. There are some papers reporting the chemical geography of pines basing upon monoterpene composition. The number of populations studied here is not enough to state this problem. The kinds of monoterpene observed in needle were ${\alpha}$-pinene, camphene, ${\beta}$-pinene, myrcene, limonene, ${\beta}$-phellandrene and terpinolene plus two unknowns. In analysis of monoterpene composition, the number of sample trees varied with population, I.e., 18 families for population 1, 15 for population 2 and 11 for population3. (Table 22, 23 and 24). The histograms(Fig. 6) of 7 components of monoterpene by population show noticeably higher percentages of ${\alpha}$-pinene irrespective of population and ${\beta}$-phellandrene in the next order. The minor Pinus densiflora monoterpene composition of camphene, myrcene, limonene and terpinolene made up less than 10 percent of the portion in general. The average coefficients of variation of ${\alpha}$-pinene and ${\beta}$-phellandrene were 11 percent. On the contrary to this, the average coefficients of variation of camphene, limonene and terpinolene varied from 20 to 30 percent. And the significant differences between populaiton were observed only in myrcene and ${\beta}$-phellandrene. (Table 25).