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The Ontology Based, the Movie Contents Recommendation Scheme, Using Relations of Movie Metadata (온톨로지 기반 영화 메타데이터간 연관성을 활용한 영화 추천 기법)

  • Kim, Jaeyoung;Lee, Seok-Won
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.25-44
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    • 2013
  • Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

Efficient Topic Modeling by Mapping Global and Local Topics (전역 토픽의 지역 매핑을 통한 효율적 토픽 모델링 방안)

  • Choi, Hochang;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.69-94
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    • 2017
  • Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

A Study on the Visions of Zechariah in the Old Testament from a Perspective of Analytical Psychology (구약성서 '스가랴'서의 환상에 대한 분석심리학적 연구)

  • Sang Ick Han
    • Sim-seong Yeon-gu
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    • v.29 no.1
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    • pp.1-45
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    • 2014
  • Mystic experience such as seeing an vision could be explained as experiencing elusive and mysterious unique existence in religious way. In depth psychology, which is based on unconsciousness like analytical psychology, this could be explained as a something that gives a meaning of life and purpose through discovering health and healing. The importance of primodial experience in depth psychology is that it can possibly discover the base of present acts. In Christian theology, symbolic mystery and truth of religious experience that appear in Christian tradition have interest on human situation. These two fields' approach methods are different, but both show common interest on unique experience which can be said properly as raw experience. Various visions appear in many parts of the Bible. Among many visions, the book of Zechariah, one of the 12 Prophets, describes rich and diverse 8 visions through chapter 1 to chapter 8. However, due to the Genre of revelation, it lacks historicity, and because of vagueness and symbolic meanings, its visions are hard to understand and interpret. Theologically, visions of Zechariah show communality of Israelites by reconstructing kingdom of Judah and church in a way of historical circumstances. Though, these visions could deliver the meaning of an ethnical aspect as reporting continuous conversation between the God and humans. Furthermore, it could mean a personal aspect of the Prophet Zechariah as reaching for a opportunity of new change. Moreover, those who read these visions could try to interpret the meanings of various images which represent meeting mysterious existences. Therefore, the Author would concentrate on the fact that 8 visions in the book of Zechariah, which has not been received much attention to neither Christians nor non-believers, develop in chiastic structure (stylistic contrast), so that tries to interpret the first, second, seventh, and the eighth visions in analytic psychology way. In visions of Zechariah, excepting the 4th vision which probably was inserted later, rest of 7 visions each shows the stage of the hours of darkness. 1st to 3rd visions represent evening, 5th vision represents deep in the night, and 6th to 8th visions represent dawn to morning. Moreover, since structure of visions arranged in chiastic way, horse appears in 1st and 8th vision, measuring rope and measure tools are used as main motif in 2nd and 7th vision. However, same motifs could have different symbolic meanings and roles as visions are formed in different situations and conditions. In the first vision, angels who ride horses look around the world and report it is calm and peaceful. Concerning the political situation back in the day, the world being calm and peaceful in the beginning of evening means that it is not ready to change to a whole new world. Psychologically, if there is no readiness to adopt new world, it means being hopeless. It is sending you a message to get out of those kinds of situation. Moreover, appearance of four angels who rode red, brown, and white horses to a myrtus tree in the valley means that it is time for individuation and it is right and good timing for changing. In second vision, you will be able to see that Israelites had long years being caught in the shadows by foreign country, and long years succumbed by the strength of four horns, which shows the progress of renewing strength and being oneness with oneself from overwhelmed situation by paternity. In seventh vision, meaning of two women bringing the godness of the sky, who were locked up in a rice basket, back to the temple in Babylon is going towards in a level of Self-actualization by separating one's ego captured excessively by matherhood and putting back to a place where it was before. In eighth vision, chariots pulled by horses are scattered far and wide, and horses which went to north had rest in the land of North. After horses and chariots are seen between two mountains of bronze with the image of Self and anima/animus. These images can be explained as the changing progress are almost completed and the God and human, in other words Self and ego are being united and is now time for rest. All of 8 visions contains the conversation between angel and Zechariah who willing to know the meaning of visions. Zechariah asks the angel actively about the meaning of visions because of his wish for Israelites to return home and rebuild church. Conversation among the God, Zechariah, who asks questions until he knows everything, an Angel, who gives answer to given questions, is conversation between ego and anima/animus. Eventually, it is a conversation between Self and ego.