  This paper presents results of various experiments carried out to improve
text retrieval of gujarati text documents. Text retrieval involves searching
and ranking of text documents for a given set of query terms. We have tested
various retrieval models that uses bag-of-words approach. Bag-of-words approach
is a traditional approach that is being used till date where the text document
is represented as collection of words. Measures like frequency count, inverse
document frequency etc. are used to signify and rank relevant documents for
user queries. Different ranking models have been used to quantify ranking
performance using the metric of mean average precision. Gujarati is a
morphologically rich language, we have compared techniques like stop word
removal, stemming and frequent case generation against baseline to measure the
improvements in information retrieval tasks. Most of the techniques are
language dependent and requires development of language specific tools. We used
plain unprocessed word index as the baseline, we have seen significant
improvements in comparison of MAP values after applying different indexing
techniques when compared to the baseline.
