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This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
The extreme success of web search engines makes keyword search the most popular search model for ordinary users. Keyword search on XML is a user friendly way to query XML databases since it allows users to pose queries without the knowledge of complex query languages and the database schema. The three main challenges faces in XML keyword search: 1) Identify the user search intention, i.e., identify the XML node types that users want to search for and search via. 2) Resolve keyword ambiguity problems: a keyword can appear as both a tag name and a text value of some node; a keyword can appear as the text values of different XML node types and carry different meanings; a keyword can appear as the tag name of different XML node types with different meanings. 3) As the search results are sub trees of the XML documents, new scoring function is needed to estimate its relevance to a given query. However, existing methods cannot resolve these challenges, thus return low result quality in term of query relevance. In this paper, we propose an IR-style approach which basically utilizes the statistics of underlying XML data to address these challenges. We first propose specific guidelines that a search engine should meet in both search intention identification and relevance oriented rankingfor search results over XML documents. Then, based on theseguidelines, we design novel formulae to identify the search fornodes and search via nodes of a query, and present a novelXML TF*IDF ranking strategy to rank the individual matches ofall possible search intentions over XML documents.
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