The purpose of this thesis is to compare five different ranking algorithms for Query expansion. The algorithms compared are f4, f4mod, porter, wpq, and emim. This is done using a TREC collection, a selection of topics, and relevance judgements. Relative recall is measured before and after the expansion of the query. The study shows that all of the algorithms manage to increase the relative recall, f4 being the one most successful..

The aim of this masters thesis is to examine Query expansion. Query expansion is the process of adding new terms to a query to improve the retrieval effectiveness. In this study the baseline query was expanded in five different modes. The first expansion strategy was formulated by the inflected terms as the system does not allow truncation, I have inflected the terms, e. g.

This thesis deals with query formulation in full text retrieval. The variables studied were Query expansion and query structur[INS: e :INS , and the aim of the thesis is to study their co-effects on retrieval performance in a probabilistic system. The expansion was made with synonyms, and the structure by expressing facets and phrases. The study was performed using QPA, Query Performance Analyzer, which includes InQuery retrieval system and a sub-collection of TREC documents with its topics. The measurement used was precision at 11 DCV points.

In Query expansion (QE) terms are added to an initial query in order to improve retrieval effectiveness. In this thesis we use QE in the sense that a reformulation of the query is done by deleting the terms in the initial query and instead replacing them with terms from the documents retrieved in the initial run. The aim of this thesis is to, in a experimental full text invironment, study and compare the retrieval result of two different Query expansion strategies in relation to each other. The following questions are addressed by the study: How do the two strategies perform in relation to each other regarding recall? What may be causing the result? Are the two strategies retrieving the same relevant documents? Two strategies are designed to simulate a searcher using automatic Query expansion (AQE) either with or without relevance feedback.

The purpose of this Masters thesis is to examine the performance of queries that are expanded by synonyms and hyponyms from Svenskt OrdNät, the Swedish version of the Princeton WordNet. Four different types of queries were constructed: a baseline query S1, the baseline query expanded with synonyms S2, the baseline query expanded with hyponyms S3 and finally the baseline query expanded with the synonyms and hyponyms used in S2 and S3. The terms for expansion were picked by hand. The queries were executed in the Query Performance Analyser QPA, a tool used in IR education and in experimental IR research for analysing and comparing the performance of individual queries. 20 topics from the test collection GP_HDINF were chosen for the experiment.

The focus of the thesis is an information search technique called manual Query expansion, which aims to improve the retrieval per-formance in a search system by adding terms to the search query. The study looks at the Query expansions done by LIS students, and the eventual beneficial effects by using a search help during the search process. The empirical data have been collected thro-ugh an experiment, with an experiment group as well as a control group. The conclusion is that the students need more education in Query expansion in order to be able to use it correctly. There are significant differences between the groups in several aspects, for example in the use of search terms, parentheses, and truncation.

This thesis examines the effects of proximity operators and Query expansion with synonyms on retrieval performance. The queries were expanded with synonyms and structured with proximity operators where the permitted distance between terms varied from 1 to 3. The expansion terms were selected from the online lexical reference system WordNet. Initial query terms were selected from 28 topics that contained compound words and were chosen on the basis of their expandibility. The English morphological analyser ENGTWOL was used for normalization of query terms.

The aim of this thesis is to examine how thesauri constructed with latent semantic indexing LSI are performing when used for Query expansion. There is a well-known problem with synonymy in information retrieval and one solution to this problem is to use a thesaurus. In this thesis thesauri are created automatically to find statistically related words and not only synonyms. LSI is a method that uses singular value decomposition SVD to reduce dimensions in a matrix and find latent relationships between words. We constructed nine thesauri and used them for Query expansion in a Swedish database, GP_HDINF.

The purpose of this thesis is to make a comparative literary study of ten laboratory experiments with different kind of sources for Query expansion terms. The experiments are grouped according to categories of term sources, which are: search results, collection dependent knowledge structures, collection independent knowledge structures and one that combines the two last mentioned sources into one. To enable a comparison all other variables were held as constant as possible. There is the improvement measured in mean average precision, which is used to measure the various sources potential. The result from the study shows a strong connection between the kind of source for the expansion term and improvement of the result.

In information retrieval there is a problem with ambiguous words. To solve this problem word sense disambiguation WSD is used. Few studies combining information retrieval and word sense disambiguation have been conducted with Swedish words. The purpose of this thesis has been divided in two. The first purpose was to examine Swedish information retrieval and disambiguation in the query phase.

This Masters thesis deals with Query expansion in an online library catalogue. The aim of the study was to compare the retrieval effectiveness of four different query types when applied to the online library catalogue of the University College of Borås. The query types were: an initial query, the initial query with right hand truncation, the initial query expanded with synonyms and finally the initial query expanded with synonyms and right hand truncation. 24 topics were formulated, and four queries for each topic were constructed. The records retrieved by the searches were judged with regard to topicality, and were judged to be non-relevant, partially relevant or relevant.

Automatic query expansion has long been studied in information retrieval research as a technique that deals with the fundamental issue of word mismatch between query and document. The purpose of this thesis is to compare the retrieval effectiveness of different strategies for automatic Query expansion. The strategies are based on local analysis of the corpus and use statistical information from the local document set to extract terms that suppose to adapt themselves to each individual search and therefore appear to be searchonyms to the index terms. The strategies compared are: association clusters, metric cluster and scalar cluster. Baseline queries of 24 topics are expanded using terms from the different clusters and searches are made.

This Master?s thesis is a comparative study of information retrieval results between three distinct search strategies in simulated automatic Query expansion in a bibliographic database. Our purpose is to investigate which of the search strategies score the most effective precision and to what extent the same relevant documents are retrieved (overlapped). A thesaurus attached to the database is used to select appropriate descriptors for the baseline query formulations which subsequently are expanded with hierarchical relations. The search strategies are s1: A baseline query with two or three descriptors, s2: The baseline descriptors combined with at least one Narrower Term, s3: The baseline descriptors combined with Narrower Term and at least one Broader Term.

The purpose of this thesis is to examine the performance of queries that are expanded by 1 inflections, 2 compound splitting and 3 inflections and compound splitting combined. For compound splitting, the morphological analyser SWETWOL was used. Queries were executed in the Query Performance Analyser, QPA, containing the InQuery system. Query terms were selected from 29 topics, all of whom containing at least one compound word. Both the queries and the documents were in Swedish.

In this Masters thesis we investigate Query expansion using an electronic thesaurus. We formed 30 topics from the library and information science field. For each topic three searches were made in the bibliographic database LISA Library and Information Science Abstracts via CSA Cambridge Scientific Abstracts. LISA has an electronic thesaurus attached. We used this thesaurus to form baseline queries, baseline queries expanded with synonyms, and baseline queries expanded with both synonyms and related terms.