• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.61-95
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• 2007

Small-and-medium sized enterprises(SMEs) represent quite a large proportion of the industry as a whole in terms of the number of enterprises or employees. However researches on information system so far have focused on large companies, probably because SMEs were not so active in introducing information systems as larger enterprises. SMEs are now increasingly bringing in information systems such as ERP(Enterprise Resource Planning Systems) and some of the companies already entered the stage of ongoing use. Accordingly, researches should deal with the use of information systems by SME s operating under different conditions from large companies. This study examined factors and mechanism inducing faithful appropriation of information systems, in particular integrative systems such as ERP, in view of individuals` active feedback-seeking behavior. There are three factors expected to affect end users` feedback-seeking behavior for faithful appropriation of information systems. They are management support, peer IT champ support, and IT staff support. The main focus of the study is on how these factors affect feedback-seeking behavior and whether the feedback-seeking behavior plays the role of mediator for realizing faithful appropriation of information systems by end users. To examine the research model and the hypotheses, this study employed an empirical method based on a field survey. The survey used measurements mostly employed and verified by previous researches, while some of the measurements had gone through minor modifications for the purpose of the study. The survey respondents are individual employees of SMEs that have been using ERP for one year or longer. To prevent common method bias, Task-Technology Fit items used as the control variable were made to be answered by different respondents. In total, 127 pairs of valid questionnaires were collected and used for the analysis. The PLS(Partial Least Squares) approach to structural equation modeling(PLS-Graph v.3.0) was used as our data analysis strategy because of its ability to model both formative and reflective latent constructs under small-and medium-size samples. The analysis shows Reliability, Construct Validity and Discriminant Validity are appropriate. The path analysis results are as follows; first, the more there is peer IT champ support, the more the end user is likely to show feedback-seeking behavior(path-coefficient=0.230, t=2.28, p<0.05). In other words, if colleagues proficient in information system use recognize the importance of their help, pass on what they have found to be an effective way of using the system or correct others' misuse, ordinary end users will be able to seek feedback on the faithfulness of their appropriation of information system without hesitation, because they know the convenience of getting help. Second, management support encourages ordinary end users to seek more feedback(path-coefficient=0.271, t=3.06, p<0.01) by affecting the end users' perceived value of feedback(path-coefficient=0.401, t=6.01, p<0.01). Management support is far more influential than other factors that when the management of an SME well understands the benefit of ERP, promotes its faithful appropriation and pays attention to employees' satisfaction with the system, employees will make deliberate efforts for faithful appropriation of the system. However, the third factor, IT staff support was found not to be conducive to feedback-seeking behavior from end users(path-coefficient=0.174, t=1.83). This is partly attributable to the fundamental reason that there is little support for end users from IT staff in SMEs. Even when IT staff provides support, end users may find it less important than that from coworkers more familiar with the end users' job. Meanwhile, the more end users seek feedback and attempt to find ways of faithful appropriation of information systems, the more likely the users will be able to deploy the system according to the purpose the system was originally meant for(path-coefficient=0.35, t=2.88, p<0.01). Finally, the mediation effect analysis confirmed the mediation effect of feedback-seeking behavior. By confirming the mediation effect of feedback-seeking behavior, this study draws attention to the importance of feedback-seeking behavior that has long been overlooked in research about information system use. This study also explores the factors that promote feedback-seeking behavior which in result could affect end user`s faithful appropriation of information systems. In addition, this study provides insight about which inducements or resources SMEs should offer to promote individual users' feedback-seeking behavior when formal and sufficient support from IT staff or an outside information system provider is hardly expected. As the study results show, under the business environment of SMEs, help from skilled colleagues and the management plays a critical role. Therefore, SMEs should seriously consider how to utilize skilled peer information system users, while the management should pay keen attention to end users and support them to make the most of information systems.

• Korean Journal of Health Education and Promotion
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• v.17 no.1
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• pp.95-113
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• 2000

The purpose of this study is to investigate the state of the dental health of adults, used self-reporting qestionnaire as objects of 923 residents living in nine districts at random among the sites of eleven town located in a County. The level of knowledge on dental health of adults in a County was 65.6 points out of 100 points, comparatively low. Accodingly, it is necessary for entire adults to have a dental health-related education and get high standard of knowledge. Especially, educational approach should be performed for groups of 40-49 years old, 50-59 years old, above 60 years old, male, no educational background, having only elementary and middle school education, not having any jobs, engaging in agriculture, doing business on their own and so on. When planning the contents of health education, one actually has to include the habit of amalgam, the factor in influencing on dental health as well as show an example such as how to brush teeth, checking point of proper brushing, how to grip toothbrush. The attitude score related to dental heath was 71.2 points out of 100 points, relatively low. Consequently, the change of attitude related the dental health among entire adults is necessary, particularily, the strategical approach is essential to change dental health connected to attitude positively for groups of male, having high school education background, office workers and the civil service. Besides, among dental health related symtoms, more that 30-40％ of objects showed negative attitude toward as the following cases; in case that plaque or food debris are attached to the teeth (40.8％), upper and lower teeth do not fit together(40.3％), you cannot sleep well because of toothache(31.0％), more than one tooth fall out(31.0％), you have loosing teeth(30.6％), the approach should be conducted to form attitude that dental care is necessry. The state of dental health through dental health related symtoms was 33.3 points out of 100 points, which was fairly satisfactory. However, dental treatment for the state of dental health should be executed in case of comparison of the dental health state according to general characteristics, the group who are above 60 years old, have elementary school education background, engage in aggriculture who are not good in dental health state as opposed to other groups. Furthermore, there should be dental care needs according to dental health related symtoms, particularly, more than 60-70％ of objects have experienced symtoms that plaque or food debris attached to the teeth, tartar is on the teeth so dental treatment should be peformed for a large number of adults. In addition, for the people who have indications that there was a cavity, more than one tooth loss, chilled teeth, toothache when chewing, loose teeth, upper and lower teeth do not fit together, you cannnt sleep well due to the toothach, etc, there should be care through dental treatment. The actual conditions of the hygine of the mouth was relatively good and the difference of the actual state of dental health care in terms of general characteristics showed in only gender; female was more careful in dental health. Comparing the state of oral health synthetically, when they have symtoms, only 34.8％ of objects go to a dentist, 60.7％ are using passive or negative care such as gargling, tolerating or ignoring. There was many symtoms to care through dental therapy such as plaque or food debris get in between the teeth, tartar on the teeth, teeth are very cold, more than one tooth fallout, loose teeth, there is wrong amalgam, and so on, among symtoms to care passively or negatively. Therefore the education for proper treatment program should be performed. As a result of dental health-related knowlege, attitude, health state, verification of correlation between the actual condition of care, the higher the dental heath-related knowldege becomes, the more positive the dental health-related attitude is, and the state of dental health, that is, the standard of the symtom of dental health diminishes. the care for dental health executed through more active method and the more positive dental health-related attitude is, the more active means they performed. Consequently, the high level of dental health-related knowledge should be necessary, the more positive the dental health-related attitude was, the more active method they adopted, therefore, the program is needed to form attitude related to the dental health positively. As the knowledge on dental health is increasing, the attitude is also positive, after all, the plan to increase the standard of knowledge on dental health should be contrived through education program related to dental health.

• The Korean Journal of Air & Space Law and Policy
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• v.4
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• pp.65-85
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• 1992

The air waybill is supposed to be made out by the consignor. If the carrier makes it out, he is deemed, subject to proof to the contrary, to have done so on behalf of the consignor. The air waybill shall be made out in three original parts. The first part shall be marked "for the carrier", and shall be signed by the consignor. The second part shall be marked "for the consignee", it shall be signed by the consignor and by the carrier and shall accompany the goods. The third part shall be signed by the carrier and handed by him to the consignor, after the goods have been accepted. According to the original Warsow Convention article 8, the air waybill must contain 17 particulars or items. However, the Hague Protocol reduced to three the number of particulars required to appear on the air waybill. Only one item is obligatory, namely, the notice that the carriage is subject to the rules of the Warsaw Convention. The absence of the air waybill entails unlimited liability of the carrier because it deprives him of the right to avail himself of the provisions of the Warsaw Convention which exclude or limit his liability. The consignor shall be liable for all damages suffered by the carrier or any other person by reason of the irregularity, incorrectness or incompleteness of the particulars and statements in the air waybill. Although the contract of the carriage of goods by air is not a formal contract, the document of carriage is issued. The issue of air wayhill is not essential for the existence or validity of the contract, but serves merely as a means of proof. The Hague Protocol has lessened the consequences of the carrier's neglect to faithfully accomplish the required formalities. Henceforth, these formalities no longer constitute legal obligations. The air waybill is the consignment note used for the carriage of goods by air. It is often called an air consignment note and is not a document of title or transferable/negotiable instrument. It is basically a receipt for the goods for despatch and is prima facie evidence of the conditions of carriage. Each of the original parts of the air waybill has evidential value and possession of his part is a condition for the exercise by the consignor or cosignee of his rights under the contract of carriage. Oveall, it is an usage that under a documentary letter of credit, the consignee on the air waybill is the opening bank of the letter of credit, and the notify party is the importer who applied for the letter of credit. In Korea there is an usage as to process of cargo delivery in air transportation as follows: The carrier carries the cargo into the bonded area of the airport and gives both the notice of arrival of the cargo and the consignee's air waybill to the notify party who is the importer. Then the notify party obtains the Letter of Guarantee from the opening bank in exchange for reimbursing the amount of the letter of credit or tendering the security therefor to the opening bank. The notify party then presents this document to the customs authorities for the process of customs clearance. The opening bank becomes a consignee only to ensure repayment of the funds it has expended, and the only interest of the opening bank as consignee is the reimbursement of the money paid to the exporter under the documentary letter of credit. Just as the bill of lading in maritime law, the air waybill has always been considered negotiable although the Warsaw Convention does not emphasize this aspect of negotiability. However, the Hague Protocol article 4 corrected the situation by stating that "nothing in this Convention prevents the issue of a negotiable air waybill." This provision officially recognizes that the air waybill must meet the needs of the present day business circles by being a negotiable instrument. Meanwhile, Montreal Additional Protocol no. 4 has brought important changes. Registration by computer is acceptable and the parties to the contract of carriage are allowed to replace the air waybill with a receipt for the goods. In conclusion, as the Warsaw Convention has not details of provisions relating to the issuing of the negotiable air waybill, it is hoped that there should be supplement to the Warsaw Convention and establishment of international commercial usage with regard to the negotiable air waybill.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.75-99
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• 2012

Innovation can come from inside or outside organizations. Recently, organizations have begun turning to external knowledge more often, through various forms of collective intelligence (CI) as collaborative platform to solve complex problems. Several factors facilitate this CI utilization phenomenon. First, with the rapid development of Internet and social media, numerous web applications have become available to millions of the Internet users over the past few decades. Web 2.0 and social media have become innovative web applications that provide an environment for human social interaction and collaboration. Second, the diffusion of simple and easy-to-use technologies that enable users to interact and design web applications without programming skills have led to vast, previously unknown amounts of user-generated content. Finally, the Internet has enabled communities to connect and collaborate, creating a virtual world of CI. In this study, web enabled CI is defined as a composed ability of individuals who are acting as a single cognitive unit to achieve common goals, think reasonably, solve problems, make decisions, carry out complex tasks, and develop creative ideas collectively through participation and collaboration on the web. Although CI plays a critical role in organizational innovation and collaboration, the dubious quality of CI is still problem that is difficult to solve. In general, the quality level of content collected from the crowd is lower than that from professionals. Thus, it is important to identify determinants of CI quality and to analyze the relationship between CI quality and its usefulness. However, there is a lack of empirical study on the quality factors of web-enabled CI. There exist a variety of web enabled CI sites such as Threadless, iStockphoto or InnoCentive, Wikipedia, and Youtube. One of the most successful forms of web-enabled CI is the Wikipedia online encyclopedia, accessible all over the world. Another one example is Naver KnowledgeiN, a typical and popular CI site offering question and answer (Q&A) services. It is necessary to study whether or not different types of CI have a different effect on CI quality and its usefulness. Thus, the purpose of this paper is to answer to following research questions: ${\bullet}$ What determinants are important to CI quality? ${\bullet}$ What is the relationship between CI quality factors and the usefulness of web-enabled CI? ${\bullet}$ Does CI type have a moderating effect on the relationship between CI quality, its determinants, and CI usefulness? Online survey using Google Docs with email and Kakao Talk was conducted for collecting data from Wikipedia and Naver KnowledgeiN users. A totoal of 490 valid responses were collected, where users of Wikipedia were 220 while users of Naver KnowledgeiN were 270. Expertise of contributors, community size, and diversity of contributors were identified as core determinants of perceived CI quality. Perceived CI quality has significantly influenced perceived CI usefulness from a user's perspective. For improving CI quality, it is believed that organizations should ensure proper crowd size, facilitate CI contributors' diversity and attract as many expert contributors as possible. Hypotheses that CI type plays a role of moderator were partially supported. First, the relationship between expertise of contributors and perceived CI quality was different according to CI type. The expertise of contributors played a more important role in CI quality in the case of Q&A services such as Knowledge iN compared to wiki services such as Wikipedia. This implies that Q&A service requires more expertise and experiences in particular areas rather than the case of Wiki service to improve service quality. Second, the relationship between community size and perceived CI quality was different according to CI type. The community size has a greater effect on CI quality in case of Wiki service than that of Q&A service. The number of contributors in Wikipeda is important because Wiki is an encyclopedia service which is edited and revised repeatedly from many contributors while the answer given in Naver Knowledge iN can not be corrected by others. Finally, CI quality has a greater effect on its usefulness in case of Wiki service rather than Q&A service. In this paper, we suggested implications for practitioners and theorists. Organizations offering services based on collective intelligence try to improve expertise of contributeros, to increase the number of contributors, and to facilitate participation of various contributors.

• International Commerce and Information Review
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• v.13 no.4
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• pp.485-516
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• 2011

Republic of Korea is small nation that is comprised of 0.7% of the world population and occupying just 0.07% of the world territory. Despite this, Republic of Korea once again proved herself to be as the world's major economic powerhouse by becoming the world's 7th largest exporter in 2010. However, the reality is that Republic of Korea is still significantly concerned about the volatile economic nature and anxiety that is spread across the globe since the global depression that began at the end of 2008 and the financial crisis that has been threatening the Euro-Zone recently. This has resulted in the nation reaching the limitation in significant economic growth and limited creation of jobs within the nation and due to such circumstances, the nation is becoming more aware of the fact that she needs to pay more attention on the service sector and service exports if she was to see a more positive economic outlook in the upcoming future. This research is aimed to analyse the cost that is associated with the service export sector, by examining a number of enterprises in relation to the MICE(Meeting Incentives Convention Exhibition) industry which certainly has both direct and indirect influences on the service exports of the nation Further, the prime goal of the research is to encourage the SMEs of Korea, who have substandard experience associated to foreign exports, to intensify and increase service exports and also the goal extends to the degree to suggest appropriate assistance measures to aid these enterprises to achieve such goals. This research is fundamentally designed and based on the literature research associated with the MICE industry and also, this research is premeditated through the analysis of the case of exports to Vietnam. As the result of research, it has been found out that SMEs in the MICE industry and those of in service export sector are reluctant or even feel insecure to attempt any kind of export of their services mainly due to; the lack of foreign market information and also the lack of experience associated with service exports. Furthermore, it has also been revealed that the difficulty to estimate the validity and profitability of service the export is a significant factor withholding those enterprises from attempting any service export to the foreign markets. Henceforth, in order to aid and stimulate service export to the foreign markets by these SMEs (including those in association with the MICE industry), it is imperative to prepare an one-stop service export assistance program which would provide the information associated with marketing, law and legislation, taxation system and financial area in regard to the global markets.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.