Query Expansion: Is It Necessary In Textual Case-Based Reasoning?

Query expansion (QE) is the process of transforming a seed query to improve retrieval performance in information retrieval operations. It is often intended to overcome a vocabulary mismatch between the query and the document collection. Query expansion is known to improve retrieval effectiveness of some information retrieval systems, however, its effect in Textual Case-based reasoning (TCBR) which is closely related to the field of Information Retrieval has not been well studied. In this research, a TCBR System intended for storage and retrieval of Frequently Asked Questions (FAQs) named FAQCase was developed. Experiments were conducted to examine the effect of synonym-based query expansion on the system. The result has shown that there is significant retrieval improvement in FAQCase with query expansion over FAQCase without query expansion, in a situation where vocabulary mismatch between new questions and the stored FAQs is high.Keywords: Query expansion, Textual case-based reasoning, Word sense disambiguation, WordNetNigerian Journal of Basic and Applied Science (2011), 19 (2): 269-27

N-GRAM BASED QUERY STRUCTURING SYSTEM FOR EFFECTIVE XML RETRIEVAL

Query structuring systems are keyword search systems recently used for the effective retrieval of XML documents. Existing systems fail to put keyword query ambiguity prob-lems into consideration during query pre-processing and return irrelevant predicate nodes. As a result, these sys-tems return irrelevant results. In this research, an XML keyword search system, called N-gram based XML query structuring system (NBXQSS) is developed to improve the performance of keyword searches. The NBXQSS uses an N-gram Based Query Segmentation (NBQS) method which interprets a user query as a list of semantic units to help resolve ambiguity. The system also introduces an improved predicate identification algorithm (IPIA) to return rele-vant predicates. The IPIA uses a proposed function to com-pute the query term proximity and ordering. The effective-ness of the NBXQS is demonstrated through experimental performance study on some real-world XML documents. The results show that the developed system performs bet-ter compared to the existing system in terms of precision