• Title/Summary/Keyword: Web Search Query

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Keyword Search and Ranking Methods on Semantic Web Documents (시맨틱 웹 문서에 대한 키워드 검색 및 랭킹 기법)

  • Kim, Youn-Hee;Oh, Sung-Kyun
    • Journal of Satellite, Information and Communications
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    • v.7 no.3
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    • pp.86-93
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    • 2012
  • In this paper, we propose keyword search and ranking methods for OWL documents that describe metadata and ontology on the Semantic Web. The proposed keyword search method defines a unit of keyword search result as an information resource and expands a scope of query keyword to names of class and property or literal data. And we reflected derived information by inference in the keyword search by considering the elements of OWL documents such as hierarchical relationship of classes or properties and equal relationship of classes. In addition, our method can search a large number of information resources that are relevant to query keywords because of information resources indirectly associated with query keywords through semantic relationship. Our ranking method can improve user's search satisfaction because of involving a variety of factors in the ranking by considering the characteristics of OWL. The proposed methods can be used to retrieve digital contents, such as broadcast programs.

A Study on the Conceptual Modeling and Implementation of a Semantic Search System (시맨틱 검색 시스템의 개념적 모형화와 그 구현에 대한 연구)

  • Hana, Dong-Il;Kwonb, Hyeong-In;Chong, Hak-Jin
    • Journal of Intelligence and Information Systems
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    • v.14 no.1
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    • pp.67-84
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    • 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.

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A Search Efficiency Improvement Method using Internal Contiguity in Query Terms (질의 내부 단어 인접도를 이용한 검색 효율 향상 기법)

  • Yoon, Soung-Woong;Chae, Jin-Ki;Lee, Sang-Hoon
    • Journal of KIISE:Databases
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    • v.35 no.2
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    • pp.192-198
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    • 2008
  • It is difficult to get relevant information on vast Web data. Search engines summarize and store Web information and show the ranked lists based on user queries affected by relative importance and user-adaptation. But these have limitation with showing user-intended information at the top priority. User intention is presented in general within query itself. In this paper, we propose the selective rankup methodology of user-intended search results based on weighting internal contiguity in query terms. With experimental results, we can find user-intended results with 75.8% probability using this simple method only, and efficiency of rerank proposed outperforms ordinary case by $13{\sim}20%$.

New Re-ranking Technique based on Concept-Network Profiles for Personalized Web Search (웹 검색 개인화를 위한 개념네트워크 프로파일 기반 순위 재조정 기법)

  • Kim, Han-Joon;Noh, Joon-Ho;Chang, Jae-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.69-76
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    • 2012
  • This paper proposes a novel way of personalized web search through re-ranking the search results with user profiles of concept-network structure. Basically, personalized search systems need to be based on user profiles that contain users' search patterns, and they actively use the user profiles in order to expand initial queries or to re-rank the search results. The proposed method is a sort of a re-ranking personalized search method integrated with query expansion facility. The method identifies some documents which occur commonly among a set of different search results from the expanded queries, and re-ranks the search results by the degree of co-occurring. We show that the proposed method outperforms the conventional ones by performing the empirical web search with a number of actual users who have diverse information needs and query intents.

SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval

  • Jo, Dae Woong;Kim, Myung Ho
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.2
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    • pp.97-104
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    • 2017
  • In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

A Prototype Model for Handling Fuzzy Query in Voice Search on Smartphones (스마트폰의 음성 검색에서 퍼지 쿼리 처리를 위한 프로토타입 모델)

  • Choi, Dae-Young
    • The KIPS Transactions:PartD
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    • v.18D no.4
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    • pp.309-312
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    • 2011
  • Handling fuzzy query in voice search on smartphones is one of the most difficult problems. It is mainly derived from the complexity and the degree of freedom of natural language. To reduce the complexity and the degree of freedom of fuzzy query in voice search on smartphones, attribute-driven approach for fuzzy query is proposed. In addition, a new page ranking algorithm based on the values of attributes for handling fuzzy query is proposed. It provides a smartphone user with location-based personalized page ranking based on user's search intentions. It is a further step toward location-based personalized web search for smartphone users. In this paper, we design a prototype model for handling fuzzy query in voice search on smartphones and show the experimental results of the proposed approach compared to existing smartphones.

Rule-based Semantic Search Techniques for Knowledge Commerce Services (지식 거래 서비스를 위한 규칙기반 시맨틱 검색 기법)

  • Song, Sung Kwang;Kim, Young Ji;Woo, Yong Tae
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.1
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    • pp.91-103
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    • 2010
  • This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

Ontology Version Control for Web Document Search (웹문서 검색을 위한 온톨로지 버전 제어)

  • Kim, Byung Gon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.3
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    • pp.39-48
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    • 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.

A Study on the Effects of Search Language on Web Searching Behavior: Focused on the Differences of Web Searching Pattern (검색 언어가 웹 정보검색행위에 미치는 영향에 관한 연구 - 웹 정보검색행위의 양상 차이를 중심으로 -)

  • Byun, Jeayeon
    • Journal of the Korean Society for Library and Information Science
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    • v.52 no.3
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    • pp.289-334
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    • 2018
  • Even though information in many languages other than English is quickly increasing, English is still playing the role of the lingua franca and being accounted for the largest proportion on the web. Therefore, it is necessary to investigate the key features and differences between "information searching behavior using mother tongue as a search language" and "information searching behavior using English as a search language" of users who are non-mother tongue speakers of English to acquire more diverse and abundant information. This study conducted the experiment on the web searching which is applied in concurrent think-aloud method to examine the information searching behavior and the cognitive process in Korean search and English search through the twenty-four undergraduate students at a private university in South Korea. Based on the qualitative data, this study applied the frequency analysis to web search pattern under search language. As a result, it is active, aggressive and independent information searching behavior in Korean search, while information searching behavior in English search is passive, submissive and dependent. In Korean search, the main features are the query formulation by extract and combine the terms from various sources such as users, tasks and system, the search range adjustment in diverse level, the smooth filtering of the item selection in search engine results pages, the exploration and comparison of many items and the browsing of the overall contents of web pages. Whereas, in English search, the main features are the query formulation by the terms principally extracted from task, the search range adjustment in limitative level, the item selection by rely on the relevance between the items such as categories or links, the repetitive exploring on same item, the browsing of partial contents of web pages and the frequent use of language support tools like dictionaries or translators.

Mining Search Keywords for Improving the Accuracy of Entity Search (엔터티 검색의 정확성을 높이기 위한 검색 키워드 마이닝)

  • Lee, Sun Ku;On, Byung-Won;Jung, Soo-Mok
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.9
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    • pp.451-464
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    • 2016
  • Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).