Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.
In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.
Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).
We desinged and evaluated a remote-sensing sex pheromone trap for real-time monitoring of Mythimna separata (Lepidoptera: Noctuidae), a migratory insect in Korea. The system consisted of a modified cone-trap with a sex pheromone lure, a sensing module based on light interruption, a signal transmission module based on code division multiple access, a main electronic board for system control, a power supply based on a solar collector, a stainless steel-pole supporting the system, and a signal collection and display system based on an internet web page. The ratio (>92%) of the actual number of insects to the signal number in the remote-sensing trap was improved by sensing only within a limited period at night on the basis of the insect's circadian rhythm, control of signal sensitivity on the basis of sensing software programming, 1-h interval for signal transmission, and adjustment of the signal transmission program. The signal occurrence pattern in the remote-sensing trap was conclusively similar (correlation coefficient, >0.98) to the actual pattern of adult occurrence in the trap. The result indicated that the remote-sensing trap based on the attraction of the sex pheromone lure for M. separata has a promising potential for practical use. Occurrence of M. separata adults was observed several times in 2011 and 2012, and the peaks were sharp.
The Science and Technology Information Service provided by the Korea Institute of Science and Technology Information (KISTI) is a service designed to allow users to easily and conveniently search and view content that is built similar to the general information service. NDSL is KISTI's core science, technology and information service, providing about 138 million content and having about 93 million page views in a year of 2019. In this paper, various insights were derived through the analysis of how science and technology information such as academic papers, reports and patents provided by NDSL is searched and utilized through web services (https://www.ndsl.kr) and search query words. In addition to general statistics such as the status of content construction, utilization status and utilization methods by type of content, monthly/weekly/time-of-day content usage, content view rate per one-time search by content type, the comparison of the use status of academic papers by year, the relationship between the utilization of domestic academic papers and the KCI index we analyzed the usability of each content type, such as academic papers and patents. We analyzed query words such as the language form of query words, the number of words of query words, and the relationship between query words and timeliness by content type. Based on the results of these analyses, we would like to propose ways to improve the service. We suggest that NDSL improvements include ways to dynamically reflect the results of content utilization behavior in the search results rankings, to extend query and to establish profile information through non-login user identification for targeted services.
KIM, Gil-Ho;CHOI, Yun-Seok;WON, Young-Jin;KIM, Kyung-Tak
Journal of the Korean Association of Geographic Information Studies
/
v.20
no.3
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pp.12-26
/
2017
The objective of this study was to develop a runoff analysis system of the Nakdong River watershed using the GRM (Grid-based Rainfall-runoff Model), a physically-based distributed rainfall-runoff model, and to assess the system run time performance according to Microsoft Azure VM (Virtual Machine) settings. Nakdong River watershed was divided into 20 sub-watersheds, and GRM model was constructed for each subwatershed. Runoff analysis of each watershed was calculated in separated CPU process that maintained the upstream and downstream topology. MoLIT (Ministry of Land, Infrastructure and Transport) real-time radar rainfall and dam discharge data were applied to the analysis. Runoff analysis system was run in Azure environment, and simulation results were displayed through web page. Based on this study, the Nakdong River real-time runoff analysis system, which consisted of a real-time data server, calculation node (Azure), and user PC, could be developed. The system performance was more dependent on the CPU than RAM. Disk I/O and calculation bottlenecks could be resolved by distributing disk I/O and calculation processes, respectively, and simulation runtime could thereby be decreased. The study results could be referenced to construct a large watershed runoff analysis system using a distributed model with high resolution spatial and hydrological data.
Seo, Jin Soon;Kim, Young Eun;Kim, An Na;Kim, Ick Tae;Son, Yun Hee;Jang, Hyun Chul
Journal of Society of Preventive Korean Medicine
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v.24
no.2
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pp.71-82
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2020
Objectives : The purpose of this study is to evaluate clinical utilization by measuring compliance with the use of mobile health applications (AtopyPHR developed in a previous study) for patients with atopic dermatitis. Methods : Based on the AtopyPHR and the input period and frequency survey results for each symptom item, a scenario for measuring compliance was derived. The study period was 4 weeks. Participants installed AtopyPHR app and Telegram app on their smartphones, conducted user training on the app, and recorded symptoms using the app for 4 weeks. At the 2nd and 4th week visits, the AtopyPHR data recorded by the user can be viewed on the web page and used for medical decision. Compliance was analyzed by the date the symptoms were recorded. Results : There were 28 participants, all (100%) were compliant, and the compliance was 96.8. The patients were 1 to 18 years old, and the average age was 8.2±5.7 years, 10 males and 18 females. The actual date of participation in recording symptoms was 28.6±0.56 on average. Compared to Week 1, compliance decreased at Week 2, and Week 4 had the highest compliance. Daily check, daily emotion, stool/urine/sleep, and meal management showed high compliance, SCORAD and quality of life were higher than required to record. Conclusions : AtopyPHR was effective in compliance. The results of this study could be used to collect personal health data in daily life through the AtopyPHR, improving participant compliance. It is considered to be meaningful because it measured the compliance with the symptom record actually recorded using the mobile app rather than a questionnaire. This study may be useful not only for personal health care but also for medical decisions, as opinions are given by experts who treat atopic dermatitis.
Currently, the rise of social tagging has changing taxonomy to folksonomy. Tag represents a new approach to organizing information. Nonhierarchical classification allows data to be freely gathered, allows easy access, and has the ability to move directly to other content topics. Tag is expected to play a key role in clustering various types of contents, it is expand to network in the common interests among users. First, this paper determine the relationships among user, tags and resources in social tagging system and examine the circumstances of what aspects to users when creating a tag related to features of websites. Therefore, this study uses tags from the social bookmarking service 'del.icio.us' to analyze the features of tag words when adding a new web page to a list. To do this, websites features classified into 7 items, it is known as tag classification related to resources. Experiments were conducted to test the proposed classify method in the area of music, photography and games. This paper attempts to investigate the perspective in which users apply a tag to a webpage and establish the capacity of expanding a social service that offers the opportunity to create a new business model.
Most traditional newspaper publishers provide online editions to counter the competition of online news providers. However, the relationship between the online and print editions of the same newspaper has not been clearly defined. Some see the online newspaper as a substitute, while others consider it a complement. A 2002 NAA online newspaper consumer survey indicated that one-third of its respondents said they were now using the print newspaper less. Others have argued that the online edition will not wipe out print consumption, and may even complement it. While the print edition offers particular advantages such as portability, less eye strain, and the tactile experience of a printed page, the online edition also offers specific advantages such as access to breaking news, continually updated information, access to old archives, etc. All these factors would tend to lower the degree of interchangeability between the products. However, recent empirical studies show that the online edition is a substitute for rather than a complement of the print edition. Still, to some print readers, the online edition provides additional value. In this paper, by capturing the two different aspects of online editions the substitute aspect and the additional value added aspect as well as other available online alternatives, we develop an analytical model to derive the optimal production and distribution strategies of both online and print editions. Confronting the "free versus fee" issue, we show that it is optimal to provide an online version of the print newspaper for free to non-print subscribers. However, the amount of free news content that the publishers need to put on the Web depends on the available alternatives on the online market. The "fee" and "free" options both have merits and demerits as well. If the publisher charges for the online version of the print newspaper, she can generate revenue from the fee charged to online readers. However, doing so will limit the size of the online audience and further reduce online advertising revenue. At the same time, by providing a high-quality online version and charging for it, the price of the print newspaper must stay low in order to lure high valued readers. On the contrary, if the publisher provides an online version of the print newspaper for free, she can obtain a larger audience for the online version. At the same time, by providing a low-quality online newspaper, the publisher can increase the print newspaper price to get more revenue from high valued offline readers, although no revenue is incoming from online version readers. Through systematic measuring of all the pros and cons, our analysis shows that the optimal option is not "fee" but "free."
Recently, rapidly increasing internet Websites are providing us with the new kinds of multimedia informations without borders acting as the center for exchanging informations. Such new media informations through the internet passes informations via light on the monitor and provides the various informations, with the differentiation from the traditional printing media, it can be searched with electronic commands in limited space. In the process of adapting the new technologies, new media has successfully responded to the fast change and the development of its needs by experiencing the trials and errors, steadily establishing the stable position with its new information transferring and exchanging methods. The representative hompage of websites of information transformations means the first page containing no lower directories and consist of titles, icons, symbols and addresses and can design them in consideration of graphical process, planning, contents and others. Such hompages are very important since the graphical images shows its visual expressions deciding the total meanings of the hompages. In this research, we have analyzed the visual factors of frequencies, ratio of areas, distributions, alignment methodologies on layouts of hompages consisting titles, icons, contents and symbols, etc. from randomly picked samples of 161 hompages of websites in the internets of various areas. Generally, the homepages are designed with graphical expressions in personal way and the feedbacks and responses of such may differs, but we think, this can be used as reference materials for the analysis of new media in objective way. Also, it can be used as the base informations for arrangement and planning of designs with the characteristics of graphics and Graphic User Interfaces in the background which are implemented over internet.
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