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An important facility to aid keyword search on XML data is suggesting alternative queries when user queries contain typographical errors. Query suggestion thus can improve users' search experience by avoiding returning empty result or results of poor qualities. In this paper, we study the problem of effectively and
semantic net which can be applied to build personalized search engine and tested with single query keyword and multi ones by three different calculating policies. The test results show that it can affect the sort of pages. The personalized search based on vocabulary semantic net improves the quality of search results greatly.
number of users with diverse characteristics and needs. Currently, many research projects or practical applications have emerged which only support single keyword search, and few of them support semantic retrieval. In this paper, we propose a model of ontology-based semantic information retrieval systems according to hybrid
models such as a vector space model, a language model and two probabilistic models. We also proposed different measures to compute textual entailment between two terms allowing us to hopefully select appropriate keywords from thesauri to expand documents or queries automatically.
, first, we consider each individual ontology and user query keywords to determine the Basic Expansion Terms (BET) using a number of semantic measures namely Density Measure (DM), Betweenness Measure (BM), and Semantic Similarity Measure (SSM). Second, we specify New Expansion Terms (NET) by Ontology Alignment (OA). Third
dictionary, is used to segment the short text questions. From the segmentation results, the keywords are extracted to obtain query target and query requirement of the question and to generate a SQL statement for data query. The method proposed in this paper can be applied to question-answering system based on database.
This work identifies relevant songs from a user's personal music collection to accompany pictures of an event. The event's pictures are analyzed to extract aggregated semantic concepts in a variety of dimensions, including scene type, geospatial information, and event type, along with user-provided keywords. These
) information content due to occurrence of a property with respect to all the properties in a description base ii) unpredictability of an association due to participation of its properties in multiple domains iii) the extent of match between user specified keywords and properties and iv) the popularity of nodes involved in a
Web has grown to a huge mass of information resource and is diverse in content. To search such rich source of information one has to be very precise in using keywords in queries to retrieve the relevant documents. Most of the queries issued to search engines are short and have ambiguous context. One way to produce
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.