Query Expansion Using PRF-CBD Approach for Documents Retrieval

نویسندگان

  • R. Rajendra Prasath
  • Sudeshna Sarkar
چکیده

Query Expansion has been widely used to improve the effectiveness of documents retrieval. In this work, we have attempted to identify additional terms for query expansion, from the initial set of documents retrieved for the original query, with the help of Clustering-by-Directions (CBD) algorithm proposed by Kaczmarek[1]. The CBD algorithm is based a tag cloud of associated terms that are located in a radical arrangement and provides a clue to the direction of user intent in which search can be continued effectively. The output of the CBD approach gives rise to a set of terms in which we have considered top k terms for expanding the given query. The importance (weighting) of these selected expansion terms are computed with respect to the number of terms in the radical of the selected directions. The experiments were conducted on FIRE 2012 adhoc data collection and we have performed monolingual documents retrieval in 3 major languages: Bengali, Hindi and English.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Relevance Feedback Based Query Expansion Model Using Borda Count and Semantic Similarity Approach

Pseudo-Relevance Feedback (PRF) is a well-known method of query expansion for improving the performance of information retrieval systems. All the terms of PRF documents are not important for expanding the user query. Therefore selection of proper expansion term is very important for improving system performance. Individual query expansion terms selection methods have been widely investigated fo...

متن کامل

External Query Reformulation for Text-Based Image Retrieval

In text-based image retrieval, the Incomplete Annotation Problem (IAP) can greatly degrade retrieval effectiveness. A standard method used to address this problem is pseudo relevance feedback (PRF) which updates user queries by adding feedback terms selected automatically from top ranked documents in a prior retrieval run. PRF assumes that the target collection provides enough feedback informat...

متن کامل

Novel Approach for Query Expansion Using Genetic Algorithm

This paper is focused towards query expansion, which is an important technique for improving retrieval efficiency of an Information Retrieval System. Specifically the paper proposes a novel evolutionary approach for improving efficiency of Pseudo Relevance Feedback (PRF) Based Query Expansion. In this method the candidate terms for query expansion are selected from an initially retrieved list o...

متن کامل

Improving Pseudo - Relevance Feedback : “ Multiple Paths , Same Goal ”

A common problem in Information Retrieval(IR) is when queries are too short to completely convey the user’s information need. A well-known technique to fix this is Query Expansion(QE), where relevant, informative terms are added to the query, to convey the missing intent. Pseudo-Relevance Feedback(PRF) is one of the popular methods to perform Query Expansion, and is widely accepted to improve r...

متن کامل

UAB at MediaEval 2011: Genre Tagging Task

We describe our approach and results towards the genre tagging task of MediaEval 2011. We approached this as an Information Retrieval task and applied a pseudo relevance feedback (PRF) approach for query expansion. Query expansion was also done using WordNet and Wikipedia

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013