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from the top-ranked documents in initial retrieval results. The other is 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
search techniques. In this paper, we introduce an associated semantic network as the semantic representation model; use semantic keywords, a linguistic ontology in semantic similarity calculation and use learner relevance feedback to complete automatic semantic annotation. After several iterations of learner relevance
When searching for information a user wants, search engines often return lots of results unintended by the user. Query expansion is a promising approach to solve this problem. In the query expansion research, one of big issues is to generate appropriate keywords representing the user's intention. This paper proposes
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.