• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.111-126
• /
• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Restorative Dentistry and Endodontics
• /
• v.27 no.5
• /
• pp.463-472
• /
• 2002

Bacterial lipopolysaccharide (LPS) plays a major role in stimulating the synthesis and release of the principal osteoclast-activating cytokines, namely, interleukin 1 and tumor necrosis factor-$\alpha$ from immune cells. Although rnonocytes/macrophages are the main producers of these cytokines, recent evidence has indicated that polymorphonuclear leukocytes (PMN) have the ability to release IL-1 and TNF-$\alpha$. Calcium hydroxide has been shown to be an effective medicament in root canal infections, reducing the microbial titre within the canal. It has been proposed that the therapeutic effect of Ca(OH)$_2$ may also be the result of direct inactivation of LPS. The purpose of this study was to investigate whether treatment of Porphyromonas endodontalis LPS with calcium hydroxide alters its biological action as measured by human PMN secretion of IL-1 and TNF-$\alpha$, and it was compared with Escherichia coli LPS. P. endodontalis ATCC 35406 was cultured in anaerobic condition, and LPS was extracted using the hot-phenol water extraction method and purified. Purchased E. coli LPS was also purified. 100 $\mu\textrm{g}$/ml of each LPS in pyrogen free water were incubated with 25mg/ml Ca(OH)$_2$ at 37$^{\circ}C$ for 7 days. The supernatants were subjected to ultrafiltration, and the isolates were lyophilized and weighed. PMNs were obtained from peripheral blood by centrifugation layered over Lymphoprep. The cells were resuspended (4$\times$10$^6$ cells/ml) in RPMI 1640 followed by treatment with various concentrations of LPS (0, 0.1, 1, 10$\mu\textrm{g}$/ml) for 24 hours at 37$^{\circ}C$ in 5% $CO_2$ incubator. The supernatants of cells were collected and the levels of IL-1$\alpha$, IL=1$\beta$ and TNF-$\alpha$ were measured by enzyme-linked immunosorbent assay. The results were as follows ; 1. The levels of IL-1$\alpha$, IL-1$\beta$, TNF-$\alpha$ from PMN treated with each LPS were significantly higher than those released from unstimulated PMN of the control group (p<0.05). 2. The levels of all three cytokines released from PMN stimulated with each calcium hydroxide treated LPS were significantly lower than those released from PMN stimulated with each untreated LPS (p<0.05), while they were not significantly different from those released from unstimulated PMN of the control group (p>0.05) 3. The levels of secretion for all three cytokines were affected in a dose-dependent manner in PMN stimulated with each LPS (p<0.05), but not in PMN stimulated with each calcium hydroxide treated LPS (p>0.05). 4. The levels of all three cytokines released from PMN stimulated with p. endodontalis LPS were significantly lower than those released from PMN stimulated with E coli LPS (p<0.05).

• Journal of Oral Medicine and Pain
• /
• v.34 no.4
• /
• pp.379-385
• /
• 2009

The purpose of this study was to present basic data that is needed in comprehension of dysesthesia after mandibular nerve injury and grasp meaning. We analyzed medical records of 59 patients who were diagnosed as dysesthesia after mandibular nerve injury from January 2007 to July 2009. The results are summarized as follows. 1. The most frequent cause was implant surgery (59%) and the most frequent injured branch of mandibular nerve was inferior alveolar nerve(81%). 2. The period passed after nerve injury showed significant interrelationship with level of pain. Visual Analogue Scale(VAS) increased from 4.82 to 6.91 after 6 month. 3. The period passed after nerve injury did not show significant interrelationship with recovery of dysesthesia. But, when conservative treatment was offered at earlier stage, ratio of patients who showed recovery of symptom tended to increase. 4. In computed tomography, level of invasion into inferior alveolar nerve canal did not show significant interrelationship with level of pain and recovery of dysesthesia. Conclusively, in the patients with dysesthesia of mandibular nerve, inferior alveolar nerve injury by dental implant surgery dominated most significant problem. Although level of invasion into inferior alveolar nerve is the most important factor to initiation of dysesthesia, there are other various factors exert more influence on the level of pain or recovery of dysesthesia. Therefore, begining conservative therapy at earlier stage is encouraged. Also, because nerve injuries can occur without direct invasion into nerve canal, so leaving enough safe space from nerve canal is needed for prevention of indirect nerve injury.

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.28 no.5
• /
• pp.375-395
• /
• 2006

Purpose: Lingual nerve (LN) damage may be caused by either tumor resection or injury such as wisdom tooth extraction, Although autologous nerve graft is sometimes used to repair the damaged nerve, it has the disadvantage of necessity of another operation for nerve harvesting. Moreover, the results of nerve grafting is not satisfactory. The nerve growth factor (NGF) is well-known to play a critical role in peripheral nerve regeneration and its local delivery to the injured nerve has been continuously tried to enhance nerve regeneration. However, its application has limitations like repeated administration due to short half life of 30 minutes and an in vivo delivery model must allow for direct and local delivery. The aim of this study was to construct a well-functioning $rhNGF-{\beta}$ adenovirus for the ultimate development of improved method to promote peripheral nerve regeneration with enhanced and extended secretion of hNGF from the injured nerve by injecting $rhNGF-{\beta}$ gene directly into crush-injured LN in rat model. Materials and Methods: $hNGF-{\beta}$ gene was prepared from fetal brain cDNA library and cloned into E1/E3 deleted adenoviral vector which contains green fluorescence protein (GFP) gene as a reporter. After large scale production and purification of $rhNGF-{\beta}$ adenovirus, transfection efficiency and its expression at various cells (primary cultured Schwann cells, HEK293 cells, Schwann cell lines, NIH3T3 and CRH cells) were evaluated by fluorescent microscopy, RT-PCR, ELISA, immunocytochemistry. Furthermore, the function of rhNGF-beta, which was secreted from various cells infected with $rhNGF-{\beta}$ adenovirus, was evaluated using neuritogenesis of PC-12 cells. For in vivo evaluation of efficacy of $rhNGF-{\beta}$ adenovirus, the LNs of 8-week old rats were exposed and crush-injured with a small hemostat for 10 seconds. After the injury, $rhNGF-{\beta}$ adenovirus($2{\mu}l,\;1.5{\times}10^{11}pfu$) or saline was administered into the crushed site in the experimental (n=24) and the control group (n=24), respectively. Sham operation of another group of rats (n=9) was performed without administration of either saline or adenovirus. The taste recovery and the change of fungiform papilla were studied at 1, 2, 3 and 4 weeks. Each of the 6 animals was tested with different solutions (0.1M NaCl, 0.1M sucrose, 0.01M QHCl, or 0.01M HCl) by two-bottle test paradigm and the number of papilla was counted using SEM picture of tongue dorsum. LN was explored at the same interval as taste study and evaluated electro-physiologically (peak voltage and nerve conduction velocity) and histomorphometrically (axon count, myelin thickness). Results: The recombinant adenovirus vector carrying $rhNGF-{\beta}$ was constructed and confirmed by restriction endonuclease analysis and DNA sequence analysis. GFP expression was observed in 90% of $rhNGF-{\beta}$ adenovirus infected cells compared with uninfected cells. Total mRNA isolated from $rhNGF-{\beta}$ adenovirus infected cells showed strong RT-PCR band, however uninfected or LacZ recombinant adenovirus infected cells did not. NGF quantification by ELISA showed a maximal release of $18865.4{\pm}310.9pg/ml$ NGF at the 4th day and stably continued till 14 days by $rhNGF-{\beta}$ adenovirus infected Schwann cells. PC-12 cells exposed to media with $rhNGF-{\beta}$ adenovirus infected Schwann cell revealed at the same level of neurite-extension as the commercial NGF did. $rhNGF-{\beta}$ adenovirus injected experimental groups in comparison to the control group exhibited different taste preference ratio. Salty, sweet and sour taste preference ratio were significantly different after 2 weeks from the beginning of the experiment, which were similar to the sham group, but not to the control group.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.179-200
• /
• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.1-27
• /
• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.