Web knowledge and Wordnet based Automatic Web Query Classification
نویسندگان
چکیده
منابع مشابه
Web knowledge and Wordnet based Automatic Web Query Classification
Web search queries are the starting point to access the contents in the WWW for most of the users. Capturing the user intent behind a query statement is crucial for any search engine and is equivalent to figuring out the category to which the query belongs to. In this paper, we analyze a classification system that uses web directory search results as an extended feature of the query. A comparis...
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Problem statement: The problem is to classify a given web query to a set of 67 target categories. The target categories are ranked based on the degree of similarity to a given query. Approach: The feature set is the set of intermediate categories retrieved from a directory search engine for a given query. Using direct mapping and Normalized Web Distance (NWD) the intermediate categories are map...
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In this paper, we address a novel method of Web query expansion by using WordNet and TSN. WordNet is an online lexical dictionary which describes word relationships in three dimensions of Hypernym, Hyponym and Synonym. And their impacts to expansions are different. We provide quantitative descriptions of the query expansion impact along each dimension. However, WordNet may bring many noises for...
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The paper describes design and implementation of a new knowledge based system for Automatic Information Retrieval DataBase (AIRDB). AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an Artificial Neural Network (ANN). The classification depends mainly on keyword indexes. A large sample set consists of 11043 web pages of several format...
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In this paper, we propose a method for multi-term query expansions based on WordNet. In our approach, Hypernym/Hyponymy and Synonym relations in WordNet is used as the basic expansion rules. Then we use WordNet Lexical Chains and WordNet semantic similarity to assign terms in the same query into different groups with respect to their semantic similarities. For each group, we expand the highest ...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2011
ISSN: 0975-8887
DOI: 10.5120/2232-2849