• Journal of Information Management
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• v.42 no.4
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• pp.155-174
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• 2011

This study aims to focus on classifying the search engine queries according to web query topic and the different user intents behind web queries. First, we classified 10,000 web query data set by topic. The results showed that there was significant differences in interesting topics across time. Also, we categorized 500 popular queries in web search engine as informational, navigational, or transactional. As a result, 82 percent of web queries are informational in nature, with about 10.8 percent for navigational and 7.2 percent for transactional. This results will help establish the policy to provide internet contents based on user's intent and also find out the social and cultural characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2468-2487
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• 2015

In web searching, trustable and precise results are greatly affected by the inherent uncertainty in the input queries. Queries submitted to search engines are by nature ambiguous and constitute a significant proportion of the instances given to web search engines. Ambiguous queries pose real challenges for the web search engines due to versatility of information. Temporal based approaches whereas somehow reduce the uncertainty in queries but still lack to provide results according to users aspirations. Web search science has created an interest for the researchers to incorporate contextual information for resolving the uncertainty in search results. In this paper, we propose an Adaptive Disambiguation Approach (ADA) of hybrid nature that makes use of both the temporal and contextual information to improve user experience. The proposed hybrid approach presents the search results to the users based on their location and temporal information. A Java based prototype of the systems is developed and evaluated using standard dataset to determine its efficacy in terms of precision, accuracy, recall, and F1-measure. Supported by experimental results, ADA demonstrates better results along all the axes as compared to temporal based approaches.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.5
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• pp.419-433
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• 2004

As XML becomes a standard for data representation, integration, and exchange on the Web, several XML query languages have been proposed. World Wide Web Consortium(W3C) has proposed XQuery as a standard for the XML query language. Like SQL, XQuery allows nested queries. Thus, normalization rules have been proposed to transform nested XQuery queries to semantically equivalent ones that could be executed more efficiently. However, previous normalization rules are applicable only to restricted forms of nested XQuery queries. Specifically, they can not handle FLWR expressions having nested expressions in the where clause. In this paper, we propose normalization rules for XQuery queries by extending those for SQL queries. Our proposed rules can handle FLWR expressions haying nested expressions in every clause. The major contributions of this paper are as follows. First, we classily nesting types of XQuery queries according to the existence of correlation and aggregation. We then propose normalization rules for each nesting type. Second, we propose detailed algorithms that apply the normalization rules to nested XQuery queries.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.79-88
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• 2015

The web search engines are exposed to the issue of uncertainty because of ambiguous queries, being input for retrieving the accurate results. Ambiguous queries constitute a significant fraction of such instances and pose real challenges to web search engines. Moreover, web search has created an interest for the researchers to deal with search by considering context in terms of location perspective. Our proposed disambiguation approach is designed to improve user experience by using context in terms of location relevance with the document relevance. The aim is that providing the user a comprehensive location perspective of a topic is informative than retrieving a result that only contains temporal or context information. The capacity to use this information in a location manner can be, from a user perspective, potentially useful for several tasks, including user query understanding or clustering based on location. In order to carry out the approach, we developed a Java based prototype to derive the contextual information from the web results based on the queries from the well-known datasets. Among those results, queries are further classified in order to perform search in a broad way. After the result provision to users and the selection made by them, feedback is recorded implicitly to improve the web search based on contextual information. The experiment results demonstrate the outstanding performance of our approach in terms of precision 75%, accuracy 73%; recall 81% and f-measure 78% when compared with generic temporal evaluation approach and furthermore achieved precision 86%, accuracy 71%; recall 67% and f-measure 75% when compared with web document clustering approach.

• Spatial Information Research
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• v.18 no.5
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• pp.83-92
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• 2010

Recently, as the Geospatial Web is combined with the Semantic Web in order to keep pace with the recent trends of information technology emphasizing interoperability, intelligence and individualization, the Geo Semantic Web was proposed, which is an intelligent geographical information Web service technology that can provide users with suitable information by connecting and integrating various types of spatial information and extensive aspatial information on the Web efficiently. For the Geo Semantic Web service, we need to develop Geo Ontology processing technologies that enable computers to process knowledge and information scattered around in the Web environment automatically. However, standards for Geo Ontology processing technologies have nod been established yet, and standardization organizations and various groups and agencies are conducting relevant studies. This paper analyzed various base theories and technologies related to Geo Ontology and developed a Geo Semantic Web system. The Geo Semantic Web system comprises Query Processing Manager that analyzes and processes Geo Semantic queries and manages sessions, Ontology Manager that generates and queries Geo Ontology and extracts spatial/aspatial data, and Clients. Finally, this paper proved the utility of the Geo Semantic Web system by applying it to a hypothetical scenario where Geo Semantic queries are required.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.1
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• pp.265-278
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• 2005

This study examines web query types and topics submitted to Naver during one year period by analyzing query logs and click logs. Query logs capture queries users submitted to the system, and click logs consist of documents users clicked and viewed. This study presents a methodology to classify query types and topics. A method for click log analysis is also suggested. When classified by query types, there are more site search queries than content search queries. Queries about computer/internet. entertainment, shopping. game, education rank hightest. The implications for system designers and web content providers are discussed.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.45-52
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• 2010

With rapid increase in the number of web documents, the problem of information overload in Internet search is growing seriously. In order to improve web search results, previous research studies employed user queries/preferred words and the number of links in the web documents. In this study, performance of the search results exploiting these two criteria is examined and other preference criteria for web documents are analyzed. Experimental results show that personalized web search results employing queries and preferred words yield up to 1.7 times better performance over the current search engine and that the search results using the number of links gives up to 1.3 times better performance. Although it is found that the first of the user's preference criteria for web documents is the contents of the document, readability and images in the document are also given a large weight. Therefore, performance of web search personalization algorithms will be greatly improved if they incorporate objective data reflecting each user's characteristics in addition to the number of queries and preferred words.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.953-957
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• 2009

This paper proposes a keyword-based query translation system for the semantic web. With the relationship between keywords and ontology structure information, the system converts keyword based queries into queries written by formal query language which is appropriate for the semantic web. As a result, casual web users could not only express queries easily but also obtain the better result.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1327-1339
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• 2023

World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.35-45
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• 2009

According to the widespread use of ontology documents, a management system which store ontology data and process queries is needed for retrieving semantic information efficiently. In this paper I propose a storage schema that stores and retrieves semantic web documents based on RDF/RDFS ontology language developed by W3C in a relational databases. Specially, the proposed storage schema is designed to retrieve efficiently hierarchy information and to increase efficiency of query processing. Also, I describe a mechanism to transform RQL semantic queries to SQL relational queries and build up database using MS-ACCESS and implement in this paper. According to the result of implementation, we can blow that not only data query based on triple model but also query for schema and hierarchy information are transformed simply to SQL.