Hİ all,<br><br>im a 4th year undergrad student in cs and im interested in aptitude search ranking implementation project.<br><br>to be fair i havent used xapian before.<br><br>my thesis topic is comparison of turkish information retrieval performance of lemur and terrier toolkits regarding their different retrieval algos.<br>
<br>i have also used lucene in my ir course so im familiar with ir and believe i can do my best for this project.<br><br>so i have some background information about the ir terms.<br><br>when it comes to what i can add to this project i see that xapian has okapi algortihm i can try to improve ranking of results by<br>
<br>try all the possible things that affect ir performance tokenization stemming may be mistypings (python - ptyhon) AND OR specific boolean queries or differently weigted queires. <br><br>also i got good results in my experiments with lemur tf-idf model weigted with a modified okapi weighing function i can try different weighing algorithms. <br>
<br>before implementing a new ranking heuristic , first i wish to try the above i mentioned but you are the professionals and i would be glad to implement some different unigram language models for xapian<br>i believe that unigrams can give better results for small queries like package names and they arent so many fluctating like in natural language words form different meanings.<br>
<br>"java sdk" --> the probability the word "sdk" coming after java will be higher than java rails may be i can do this by modelling collection , here as my collection filenames in the repository their explanations.<br>
<br>may be we can create two fields one for filename and other for explanations of the package and its job , then can combine these two fields in search.<br><br>please dont hesitate to write your feedbacks either bad or good.<br>
<br>i really wish to work on this project and i hope i could explain myselft well.<br><br>tnx,<br><br>Emre <br>