Structural Query Expansion Based on Weighted Query Term for XML Documents

Abstract

Abstract:The main reason of low precision in information retrieval (IR) is that it is difficult for the users to submit a precise query expression for their query intensions. Furthermore, XML documents have characteristics not only in the content, but also in its structure. Therefore it is more difficult for users to submit precise query expressions. In order to solve this problem, this paper puts forward a new query expansion method based on relevance feedback. It can help users to construct a content and structure query expression which can satisfy users' intentions. This method includes two steps. The first step is to expand keywords for finding the weighted keyword which can represent the user's intentions. The second step is structural expansion based on the weighted keywords.Finally a full-edged content-structure query is formalized. Experimental results show that the method can obtain better retrieval results. The average precision of prec@10 and prec@20 is 30% higher than the original query.

A Novel XML Document Retrieval Method

“…Because XML has the characteristics of structure, easy expansibility and crossing-platform, which has gradually become the main format of information storage and exchange, and XML document has also rapidly grown accompany with it [1]. At present, XML document has been widely used in the field of scientific databases, digital libraries, the internet and other field, how to efficiently and accurately query massive data has become the very meaningful research topic in information retrieval field [2][3][4]. The accuracy of retrieval results depends on whether query expression of information retrieval or not.…”

Study on XML Retrieval Results Classification

“…Existing search engines usually return a long list of search results ranked by their relevancies to a given query, which is often tedious and less efficient. Some researches [1][2][3] imply that retrieval results are improved greatly after introducing relevance feedback mechanism, and classification or clustering on retrieval results often be used to serve relevance feedback for search engine.…”

Query Expansion Based On Both Long-Term And Short-Term Social Relation In XML Social Book Search

“…Query expansion based on a knowledge resource focuses on finding the words that are meaningfully similar with or are hypernyms / hyponyms of the original query words; this could sometimes improve the recall ratio but yet couldn"t get the user"s real intent pages especially when the query words are not clear. Query expansion based on user search log or user feedback uses statistic feature between query words and other words appeared in all users" search history, but sometimes it could expand overly [5].…”