• Journal of KIISE:Software and Applications
• /
• v.32 no.3
• /
• pp.202-214
• /
• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• The Journal of Society for e-Business Studies
• /
• v.21 no.4
• /
• pp.1-14
• /
• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.5
• /
• pp.1097-1104
• /
• 2011

In this paper, we propose a semantic web approach for personalized book recommendation. Our approach takes advantage of the content-based recommendation and improves its disadvantage that users should input their interesting fields into all book search systems they use. Our approach provides the sharing of users' profile with their interesting fields by enabling user's interesting fields to be described over each book classification ontology of various book information providers. We also provide a middleware that manages users' profiles written in RDF and analizes similarity between user's interesting field and each concept over the book classification ontology. Our approach provide better performance than traditional keyword-based search by sharing the user's profile among book recommendation systems.

• Journal of Intelligence and Information Systems
• /
• v.14 no.1
• /
• pp.67-84
• /
• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.3
• /
• pp.39-48
• /
• 2013

Ontology has an important role in semantic web to construct and query semantic data. When system make changes to ontologies, questions arise about versioning of these changes. Applying this changes on a dynamic environment is even more important. To apply these changes, change specification method is needed. Early studies show RDF-based syntax for the operations between old and new ontologies. When several ontology versions can be used for some query, if possible, using possible newest version ontology with prospective use is best way to process the query. Prospective use of ontology means using a newer version of an ontology with a data source that conforms to a more recent ontology. In this paper, for prospective use of ontology version, structure of change specification of class and property through several ontology versions is proposed. From this, efficient adaptive ontology version selection for a query can be possible. Algorithm for structure of version transition representation is proposed and simulation results show possible newest version number for queries.

• Journal of Digital Convergence
• /
• v.17 no.1
• /
• pp.209-217
• /
• 2019

In this paper, the purpose of this paper is to lay the foundation for the search system by using and building an online search engine suitable for the search domain and enabling search, conversion, integration and sharing of information. It is to use the ontology to infer hierarchical relationships, deduce objects based on that layer, and extract attributes to search areas that are relevant to the data that the user wants. In order to search for information in this way, the information search system was implemented by entering key words related to 'qualifications'. The implemented system arranged the meaning and relationship of each attribute online so that the general public can search information quickly, easily, and accurately. In addition, the implementation results were compared with two different search engines. Comparable search engines are Naver and Daum, the two major search engines. The search engine of this study, which was built using an ontology suitable for the search domain to perform searches using the semantic web, was evaluated to have excellent results. However, it is thought that a more formalized online location is necessary to increase the accuracy and reliability of search engines and to include more comprehensive categories of search terms.

• Journal of Intelligence and Information Systems
• /
• v.12 no.3
• /
• pp.95-110
• /
• 2006

To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.1 s.45
• /
• pp.17-24
• /
• 2007

Critical practicality problems are cause to search the presentation and contents according to user request and purpose in previous internet system. Recently, there are a lot of researches about dynamic adaptable ontology based system. We designed ontology based educational system which uses discrete probability and user profile. This system provided advanced usability of contents by ontology and dynamic adaptive model based on discrete probability distribution function and user profile in ontology educational systems. This models represents application domain to weighted direction graph of dynamic adaptive objects and modeling user actions using dynamically approach method structured on discrete probability function. Proposed probability analysis can use that presenting potential attribute to user actions that are tracing search actions of user in ontology structure. This approach methods can allocate dynamically appropriate profiles to user.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.8B
• /
• pp.549-561
• /
• 2005

As Internet and network technologies have been developed, e-commerces are getting more complex and more various. This paper, for meta-data and data exchange between heterogeneous database systems, uses XML schema proposed in W3C, and XML schema can present meta-data and data of relational database system as XML document format which is structural. It supports various primitive data formats, so that it uses the structure which reflects adequately data formats which relational database system offered. However, current e-commerces use heterogeneous platforms, so difficulties that is mutual interchange and management exist. For the solution for these problems, a standard ontology which defines relations of product classifications and the standard of property expression and the location ontology which offers e-commerce's information about products are constructed. Applying these ontology information to search system, by offering information which customers need efficient search is performed. Combining these ontologies and product classification category information, called XMDR, this XMDR is introduced into product search system, so this paper proposes to construct ontology server method for efficient search.

• Journal of Internet Computing and Services
• /
• v.13 no.1
• /
• pp.107-115
• /
• 2012

In recent Information Environment, various Multimedia contents are getting noticed. But, since these contents have various formats of representation and very wide range of information, it was difficult to retrieve contents that user wanted and to utilize it. To solve these problems, many studies presented draft standards for adding metadata to contents, and then, semantic search for contents had become available. Unfortunately, as the number of metadata standards and contents increased, the lack of interoperability between contents was begun and users are faced with difficulty of search contents again. To improve these problems, this paper supports interoperability between metadata standards and expands the semantic relationship between elements and proposes an ontology which is named TOFIC(The Ontology For Imagery Contents) for enhanced semantic search. In TOFIC, the semantic relationships between MPEG-7 and TV-Anytime are classified, and extended new semantics are defined. As a result, semantic search for multimedia contents is enhanced and it is possible to retrieve most of the multimedia contents that exist on the current information environment consistently. In addition, it supports enhanced content-based search for multimedia contents.