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commonly used are based on keywords, wherein provided keyword list doesn't consider the semantic relationship between keywords nor it consider the meaning of words and phrases. With such system, users frequently have problems expressing their information needs and translation those needs into requests. To overcome the
domain ontology to reformulate the user query. We proposed to reformulate the query (initially in natural language) by replacing it with the terms retrieved from ontology. Then we improve the approach by combining the terms from ontology with keyword/s extracted from the initial user's natural language query. Precision
employed in query reformulation process. This work proposes the use of crop characteristic category element in reformulating query, as well as combination with ontology and query keyword elements. The experimental results show that the use of crop characteristic category in reformulating query has significantly improved the
distributed inverted index by concept for documents. Based on them, semantic search is implemented with inference technique of Description Logic between concept descriptions of documents and query. Simulation experiments show that our approach is much higher on retrieval perform than traditional method of literal keywords
Most existing systems of information retrieval are limited to a search by keywords, based on the syntactic content of documents. The absence of semantics conducts to a very complex formulation of queries which generates the problem of access to relevant information on the web. In this paper, we implement a conversion
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.