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Keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying
Recently, with the amount of available textual data in spatial databases growing rapidly, more and more applications are required to support both spatial joins and keyword-based text information retrieval. In this paper, we discuss a new type of query, called as SJIRKS, which efficiently integrates spatial join on
Keyword search provides a simple yet effective way for the users to query and explore the underlying documents. In the recent years, there have been a great deal of research and development activities on extending keyword search capabilities to handle relational data, the dominant form in which business data are
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs. Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs.Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
the interfaces of web services, we make operations defined in WSDL files which compose web services as the base units for searching and organize all information of operations and corresponding components as documents, which will facilitate IR-Style keyword searching. In order to improve the precision of searching, we
Efficient discovery of information based on partially specified and misspelled query keywords is a challenging problem in large scale peer-to-peer (P2P) networks. This paper presents QPM, a P2P search mechanism for efficient information retrieval with misspelled and partial keywords. QPM uses the double metaphone
needs. In this paper, we present the design, architecture and implementation of an open-source keyword-based paradigm for the search of software resources in Grid infrastructures, called Minersoft. A key goal of Minersoft is to annotate automatically all the software resources with keyword-rich metadata. Using advanced
multilingual information where backend will be English database and front-end uses local languages like Hindi, Marathi or Gujrathi. Our system provides an interface to enter a keyword in local language, the keyword will be parsed, query will be formed and display the result in local language. We had developed an efficient
The field of Information Retrieval plays an important role in searching on the Internet. Most of the information retrieval systems are limited to the query processing based on keywords. In information retrieval system the matching of the query against a set of text record is the core of the system. Retrieval of the
Finding relevant documents in digital libraries has been a well studied problem in information retrieval. It is not uncommon to see users browsing digital collections without having a clear idea of the keyword search that they should perform. However, we believe that such initial query search is not totally
FCA, a session interest concept is defined as a pair of extent and intent where the extent covers a set of documents selected by the user among the search results and the intent covers a set of keyword features extracted from the selected documents. And, in order to make a concept network grow, we need to calculate the
relevance weight between each query term and its relevant terms extracted from the snapshot of Google search result when that query term is used as search keyword. The estimated relevance weights are used to select good expansion terms for second retrieval. The experiments on the two test collections show that our query
information. Keyword based information retrieval technique helps in improving recall of user query result, but having low precision. To improve precision, we adopt semantic information retrieval technique. We are proposing architecture for semantic based information retrieval, in which plain text is read semantically and the
In recent years, the application of ontology has been already toward the diversification under the development of the semantic Web technology. The main application of ontology is information retrieval. With the utilization of ontology, we expect to offer more correct information for users. Although, most of the applications of ontology are information retrieval but they lacks of the interaction with...
This paper described our development dialog system on Kyoto tourist information assistance. Dialog part of our system helped user to make an appropriate query. Information analysis part would be assisted for user to select the retrieved information. Nowadays we can get most information through the Internet. However, we have a trouble to pick up expected information from the huge results with conventional...
Due to the rapid growth of Web pages available on the Internet recently, searching a relevant and up-to-date information has become a crucial issue. Conventional search engines use heuristics to determine which Web pages are the best match for a given keyword. Results are obtained from a database that is located at
focusing on a pair of or a set of associated keywords offered by user, instead of same meaning. Generally, we would probably adopt the association rule to solve the problem. Nonetheless, the keywords or terms sets extracted from huge queries often contain sparse information composed of a wide range of keywords, with each term
weight of every sentence in a topic block is calculated in view of query keywords. Finally, several important sentences are dynamically extracted to compose the digest according to expected compression ratio with the improved maximal marginal relevance method, which can remove redundant information in summary. The
Clients' queries upon keywords or other informed description do not usually provide complete and unambiguous retrieval of information. Expansion of the queries based on semantic relation and phrase patterns is an effective approach to improve the retrieval. In this paper, a novel approach to queries expansion is
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