• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.8
• /
• pp.3070-3075
• /
• 2010

Through Web 2.0 days, the end users express their opinions and thoughts for blogs and community spaces on the Internet. These opinions and thoughts are used to purchase products, however, users only refer to a few comments not overall opinions. Opinion Analysis System is an opinion search, developed from a natural language search, which analyzes the product's positive or negative evaluations using opinions of products and services on the Internet. In this paper, we suggest a syntactic analysis and inverse processing system that studies and processes 'Positive', 'Negative', 'Neutral' in addition to 'Inverse' information to analyze 'positive' or 'negative' for the core of sentences in Opinion Analysis Service.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.6
• /
• pp.1354-1359
• /
• 2013

With the development of multimedia and network technology, the production of multimedia contents is rapidly increasing. Meanwhile, the technology to search and use the contents is still insufficient. There are standards for multimedia contents to address the problem, but they cannot fully support diverse multimedia data types or ensure their interoperability. In this paper, an ontology-based content search system is proposed to ensure the interoperability of multimedia contents. The ontology is configured by presenting the rules for it using the schema structure of the multimedia description scheme (MDS) of MPEG-7. Based on this ontology, This paper extend multimedia relationship based on ontology, thus established the semantic retrieval system.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.4
• /
• pp.96-101
• /
• 2010

The core study of semantic web is the efficiency of ontology parsing. The ontology parsing and inference is based on the significant information retrieval which is the ultimate purpose of semantic web. However, most existing ontology writing tools were not processing the efficient ontology parsing. Therefore, we design the two steps ontology parser for extracting the all facts, are included in the ontology, more fast in this study. In the first step, the token extractor collects the all tokens of ontology and the triple extractor extracts the statements in the collected tokens. In conclusion, we confirm that which is designed in this study, processes the ontology parsing more faster than the existing ontology parsers.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.5
• /
• pp.25-30
• /
• 2018

Recently with the development of Internet technology, a lot of research area such as retrieval and extracting data have getting important for providing the information efficiently and quickly. Especially, the technique of analyzing and finding the semantic similar words for given korean word such as compound words or generated newly is necessary because it is not easy to catch the meaning or semantic about them. To handle of this problem, word clustering is one of the technique which is grouping the similar words of given word. In this paper, we proposed the korean language clustering technique that clusters the similar words by embedding the words using Word2Vec from the given documents.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.4
• /
• pp.25-31
• /
• 2007

An automatic term-network construction system is proposed in this paper. This system uses the statistical values of the terms appeared in a document corpus. The 186 oral history documents collected from the Saemangeum area of Chollapuk-do, Korea, are used for the research. The term relationships presented in the term-network are decided by the cosine similarities of the term vectors. The number of the terms extracted from the documents is about 1700. The system is able to show the term relationships from the term-network as quickly as like a real-time system. The way of this term-network construction is expected as one of the methods to construct the ontology system and to support the semantic retrieval system in the near future.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.12
• /
• pp.2603-2608
• /
• 2009

Document clustering is an important method for document analysis and is used in many different information retrieval applications. This paper proposes a new document clustering model using the clustering method based NMF(non-negative matrix factorization) and refinement of documents in cluster by using coherence of cluster. The proposed method can improve the quality of document clustering because the re-assigned documents in cluster by using coherence of cluster based similarity between documents, the semantic feature matrix and the semantic variable matrix, which is used in document clustering, can represent an inherent structure of document set more well. The experimental results demonstrate appling the proposed method to document clustering methods achieves better performance than documents clustering methods.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2005.05a
• /
• pp.316-320
• /
• 2005

We developed Intelligent Product Search Agent based on SWRL, and this agent can search product information with knowledge(facts and rules) on the web, implement price comparison for searched products considering delivery rates. Existing keyword based product search engines is poor at searching intent products though a user has already prefect knowledge about intent produces. Furthermore if a user has insufficient knowledge, it is impossible to implement search. Also, existing price comparison shopping mall gives users comparison service considering total price(product prices, taxes, delivery rates), this service is valid to single product and has limitations of system expansion and up-dating because of not rule base but programming base. If there is appropriate knowledge on the Semantic web and this makes product information retrieval possible, above problems can be solved clearly. In this research, we developed Intelligent Product Search Agent based on SWRL that can search product information efficiently by making agent to handle facts and rules by itself.

• Journal of Korea Multimedia Society
• /
• v.10 no.5
• /
• pp.559-568
• /
• 2007

Anchor-person scene detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper proposes an efficient algorithm extracting anchor ranges that exist in sports news video for unit structuring of sports news. To detect anchor person scenes, first, anchor person candidate scene is decided by DCT coefficients and motion vector information in the MPEG4 compressed video. Then, from the candidate anchor scenes, image processing method is utilized to classify the news video into anchor-person scenes and non-anchor(sports) scenes. The proposed scheme achieves a mean precision and recall of 98% in the anchor-person scenes detection experiment.

• Journal of Korean Library and Information Science Society
• /
• v.12
• /
• pp.61-96
• /
• 1985

The human subject analysis of a document has some critical problems. The method results in the inconsistency in analysis process and the contradiction of two objects of the subject analysis (one is the identification of the content for the retrieval of specific items and the other is to identify the content for the grouping of related materials). Since the subject analysis by mechanized has been recognized to be the possible way to aggregate the problems of manual analysis, various a n.0, pproaches of automatic indexing have been studied and experimented. This study is to examine the automatic indexing as one of the promising subject analysis techniques by statistical, syntactical and semantic a n.0, pproaches. In conclusion, the reasonable a n.0, pplication time of the automatic indexing should be made a decision based on the through investigation on the cost verse effectiveness, and automatic indexing system should be developed in the close relationship with the on-line search which is a good retrieval system for information explosion society. From now on, since the machine-readable document-text will be envisaged to be more and more available due to the rapid development of computer technology, the more substantial research on the automatic indexing will be also possible, which can bring about the increasing of practical automatic indexing systems.

• Journal of Internet Computing and Services
• /
• v.11 no.3
• /
• pp.15-24
• /
• 2010

In this paper, we propose an image classification which combines semantic relations of tags with contents of images to improve the satisfaction of image retrieval on application domains as huge image sharing sites. To make good use of image retrieval or classification algorithms on huge image sharing sites as Flickr, they are applicable to real tagged Web images. To classify the Web images by 'bag of visual word' based image content, our algorithm includes training the category model by utilizing the preliminary retrieved images with semantically related tags as training data and classifying the test images based on PLSA. In the experimental results on the Flickr Web images, the proposed method produced the better precision and recall rates than those from the existing method using tag information.