This Master’s thesis examines different retrieval strategies used in cross-language information retrieval (CLIR). The aim was to investigate if there were any differences between baseline queries and translated queries in retrieval effectiveness; how the retrieval effectiveness was affected by query structuring and if the results differed between different languages. The languages used in this study were Swedish, English and Finnish. 30 topics from the TrecUta collection were translated into Swedish and Finnish. Baseline queries in Swedish and Finnish were made and translated into English using a dictionary and thereby simulating automatic translation. The queries were expanded by adding all the translations from the main entries to the queries. Two kinds of queries – structured and unstructured – were designed. The queries were fed into the InQuery IR system which presented a list of retrieved documents where the relevant ones were marked. The performance of the queries was analysed by Query Performance Analyser (QPA). Average precision at seen relevant documents at DCV 10, average precision at DCV 10 and precision and recall at DCV 200 were used to measure the retrieval effectiveness. Despite the morphological differences between Swedish and Finnish, none or very small differences in retrieval performance were found, except when average precision at DCV 10 was used. The baseline queries performed the best results and the structured queries performed better in both Swedish and Finnish than the unstructured queries. The results are consistent with previous research. / Uppsatsnivå: D

This thesis compares four relevance feedback methods. The Rocchio and Ide dec-hi algorithms for the vector space model and the binary independence model and Okapi BM25 within the probabilistic framework. This is done in a custom-made Information Retrieval system utilizing a collection containing 131 896 LA-Times articles which is part of the TREC ad-hoc collection. The methods are compared on two grounds, using only the relevance information from the 20 highest ranked documents from an initial search and also by using all available relevance information. Although a significant effect of choice of method could be found on the first ground, post-hoc analysis could not determine any statistically significant differences between the methods where Rocchio, Ide dec-hi and Okapi BM25 performed equivalent. All methods except the binary independence model performed significantly better than using no relevance feedback. It was also revealed that although the binary independence model performed far worse on average than the other methods it did outperform them on nearly 20 % of the topics. Further analysis argued that this depends on the lack of query expansion in the binary independence model which is advantageous for some topics although has a negative effect on retrieval efficiency in general. On the second ground Okapi BM25 performed significantly better than the other methods with the binary independence model once again being the worst performer. It was argued that the other methods have problems scaling to large amounts of relevance information where Okapi BM25 has no such issues. / Uppsatsnivå: D