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The integration of the classical Web (of documents) with the emerging Web of Data is a challenging vision. In this paper we focus on an integration approach during searching which aims at enriching the responses of non-semantic search systems (e.g. professional search systems, web search engines) with semantic information, i.e. Linked Open Data (LOD), and exploiting the outcome for providing an overview...
Given a set of keywords, we find a maximum Web query (containing the most keywords possible) that respects user-defined bounds on the number of returned hits. We assume a real-world setting where the user is not given direct access to a Web search engine's index, i.e., querying is possible only through an interface
Search engine marketing provided by search engines enable companies to promote their products to internet users based on their queries is now a major online advertising channel. In most search-based advertising services, advertisers could have dozens of keywords for the same product or service, and in most instances
Search engines usually return relevant sorted results based on the keywords. Because of the lack of considering the user's current search interest and intention, this kind of strategy may not meet users' personalized search requirements. In order to retrieve results associated with the user's current search interest
In order to improve performance of existing information retrieval technology based on keyword matching, this paper introduces a framework of multi-agent information retrieval system based on ontology according to ontology theory and multi-agent theory. The design thought of system, functions of every agent
pyramid refers to publications that belong to a most-specific research topic. In this paper, we present elGiza, a research-pyramid based search tool for VLDLs. elGiza is equipped with (i) a research-pyramid-based Content-Based Search-Keyword Suggester that helps user develop search terms to reduce search failures, and (ii) a
used to associate portions of the EMR document with concepts defined in a domain ontology. In this paper we present the XOntoRank system which tackles the problem of ontology-aware keyword search on XML documents with a particular focus on EMR XML documents. Our running examples and experiments use the Health Level Seven
prefer to eat, approximated budget for each person and few other defined parameters as searching keyword. While searching, the system will fetch the entries from the database according to user defined parameters, convert each item's metadata to fuzzy parameters and pass the list to a fuzzy controller. Then the controller
It has become common to search necessary services and contents using the Internet, but it is difficult to find exactly what one is looking for through keywords as each service is described in just too many ways. We developed "laddering" search service system that matches the needs of the users with the search targets
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.