There are considerable evidences that trained users can achieve a good search eeectiveness through structured boolean queries rather than simple keyword queries because boolean operators can help to make more accurate representations of users' information search needs. However, it is not normally easy for ordinary users to construct eeective boolean queries using appropriate boolean operators. ...

The interest for information retrieval has existed long before the Internet. Boolean retrieval is the most simple of these retrieval methods and relies on the use of Boolean operators. The terms in a query are linked together with AND, OR and NOT. This method is often used in search engines on the Internet because it is fast and can therefore be used online. This method has also its problems. T...

This paper describes and evaluates a retrieval scheme, or more precisely an additional retrieval mechanism based on interdocument relationships, that can be integrated in almost all existing retrieval schemes (e.g., Boolean, hybrid Boolean, vector-processing or probabilistic models). The intent of our approach consists of inferring knowledge about document contents based on the relevance assess...

This paper describes the retrieval approach that Berkeley used in the INEX evaluation. The primary approach is the combination of a probabilistic methods using a Logistic regression algorithm for estimation of collection relevance and element relevance, along with Boolean constraints. The paper also discusses our approach to XML component retrieval and how component and document retrieval are c...

The conventional fuzzy set model uses the MIN and MAX operators for the evaluation of boolean operators AND and OR, respectively. It has been criticized to generate incorrect ranked output in many cases. This is because the MIN and MAX operators do not well correspond with human behavior for document ranking. There are a variety of fuzzy operators to replace the MIN and MAX operators. In this p...

Based on the idea that the closer the query terms in a document are, the more relevant this document is, we propose a information retrieval method based on a fuzzy proximity degree of term occurences to compute document relevance to a query. Our model is able to deal with Boolean queries, but contrary to the traditional extensions of the basic Boolean information retrieval model, it does not ex...

Leading text extracts created to support some online Boolean retrieval goals are evaluated for their acceptability as news document summaries. Results are presented and discussed from the perspective of commercial summarization technology needs.

Searching for relevant documents is a laborious task involved in preparing systematic reviews of biomedical literature. Currently, complex Boolean queries are iteratively developed, and then each document of the final query result is assessed for relevance. However, the result set sizes of these queries are hard to control, and in practice it is difficult to balance the competing desires to kee...