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The temporal information is an essential attribute in the web page, such as the publish time and the content time in the web page. However, the major search engine does not have more view on the temporal information of web page, and ignored the relationship between the keywords and time phrases. In this paper, we focus on the need in time phrases recognizing and extracting from the web page. We built...
Question Answering Systems have emerged as a good alternative to search engines where they produce the desired information in a very precise way in the real time. However, one serious concern with the Question Answering system is that despite having answers of the questions in the knowledge base, they are not able to retrieve the answer due to mismatch between the words used by users and content creators...
Health disparities are gap in health status driven by social inequities. The differences have affected how many people get sick or how often diseases cause death. In order to reduce the health disparities, many research projects have been led by National Institutes of Health. In this paper, we propose a user-centered query expansion model that assists the health disparity researches. The proposed...
In this paper, we examine the significance of expansion of the user query by two techniques namely Efficient Clustering-By-Direction and Theme Clustering. These two techniques produce the clusters of keywords extracted from the set of retrieved documents for the user query. The former clustering is based on statistical approach whereas the latter clustering is based on semantic approach. Empirical...
In this paper we introduce an algorithmic approach, capable of creating a semantic network with concatenated terms and phrases (hash tags) from collectively postings on the Twitter sphere. This network could be exploited for query expansion provision in respect to users¢ information needs, without considering any other prior knowledge or access in search logs or browsing history records. For evaluation...
Adaptive query expansion (QE) allows users to better define their search domain by supplementing the original query with additional terms related to their preferences and information needs. The system we present is an extension of the traditional QE techniques, which rely on the computation of two-dimensional co-occurrence matrices. Our system makes use of three-dimensional co-occurrence matrices,...
Most researches on Image Retrieval (IR) have aimed at clearing away noisy images and allowing users to search only acceptable images for a target object specified by its object-name. We have become able to get enough acceptable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its...
Keyword based search scheme imposes the problem of representing a lot of web pages in the search engines. Query expansion with relevant words increases the performance of search engines, but finding and using the relevant words is an open problem. In this research we describe a new model for query expansion which employs user context and semantic concepts to discover new words for obtaining accurate...
In the context of medical document retrieval, users often under-specified queries lead to undesired search results that suffer from not containing the information they seek, inadequate domain knowledge matches and unreliable sources. To overcome the limitations of under-specified queries, we utilize tags to enhance information retrieval capabilities by expanding users' original queries with context-relevant...
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