Pseudo relevance feedback is empirically known as a useful method for enhancing retrieval performance. For example, we can apply the Rocchio method, which is well-known relevance feedback method, to the results of an initial search by assuming that the top-ranked documents are relevant. In this paper, for searching the NTCIR-3 patent test collection through pseudo feedback, we employ two releva...

Retrieval effectiveness depends on both the retrieval model and how terms are extracted and indexed. For Chinese, Japanese and Korea text, there are no spaces to delimit words. Indexing using hybrid terms (i.e. words and bigrams) was not very effective in NTCIR-II open evaluation. In this evaluation, we found that using the 2-Poisson model with hybrid term indexing can be effective in retrieval...

Similarity browsing is a useful addition to any document retrieval system including web search engines. Some already provide such functionality via links called “Find-Similar” or “Similar pages”. As a search tool, similarity browsing resembles the iterative use of relevance feedback. Therefore, the effectiveness of similarity browsing is compared to that of relevance feedback. The results show ...

The University of Otago submitted runs to the Snippet Retrieval Track and the Relevance Feedback tracks at INEX 2011. Snippets were generated using vector space ranking functions, taking into account or ignoring structural hints, and using word clouds. We found that using passages made better snippets than XML elements and that word clouds make bad snippets. In our runs in the Relevance Feedbac...

We introduce a novel relevance feedback method for contentbased image retrieval and demonstrate its effectiveness using a subset of the Corel Gallery photograph collection and five low-level colour descriptors. Relevance information is translated into updated, analytically computed descriptor weights and a new query representation, and thus the system combines movement in both query and weight ...

Relevance feedback is one method for creating a ‘virtuous cycle’ as put by Baeza-Yates between semantics and search. Previous approaches to search have generally considered the Semantic Web and hypertext Web search to be entirely disparate, indexing and searching over different domains. While relevance feedback have traditionally improved information retrieval performance, relevance feedback is...

The goal of the Rutgers TREC-6 Interactive Track study was to compare the performance and usability of a system offering positive relevance feedback with one offering positive and negative relevance feedback. Our hypothesis was that the latter system would better support the aspect identification task than the former. Although aspectual recall was higher for the system supporting both kinds of ...

Medical image retrieval can assist physicians in finding information supporting their diagnosis. Systems that allow searching for medical images need to provide tools for quick and easy navigation and query refinement as the time for information search is often short. Relevance feedback is a powerful tool in information retrieval. This study evaluates relevance feedback techniques with regard t...

Users of online search engines often find it difficult to express their need for information in the form of a query. However, if the user can identify examples of the kind of documents they require then they can employ a technique known as relevance feedback. Relevance feedback covers a range of techniques intended to improve a user’s query and facilitate retrieval of information relevant to a ...

This paper describes our work at the sixth NTCIR workshop on the subtask of invalidity search for patent retrieval. We compared different patent surrogates for their effectiveness on invalidity search. Our preliminary results show that the query by the Claims field plus PRF (pseudo relevance feedback) leads to the best results in terms of relevance degree A while the query by all free-text fiel...