The cluster hypothesis states: closely related documents tend to be relevant to the same request. We exploit this hypothesis directly by adjusting ad hoc retrieval scores from an initial retrieval so that topically related documents receive similar scores. ...

Typical pseudo-relevance feedback methods assume the top-retrieved documents are relevant and use these pseudo-relevant documents to expand terms. The initial retrieval set can, however, contain a great deal of noise. In this paper, we present a cluster-based ...

User profiles are important in personalized Web information gathering and recommendation systems. The current user profiles acquiring techniques however suffer from some problems and thus demand to improve. In this paper, a survey of the existing user ...

Local feedback for ad hoc retrieval typically hurts performance for about one-third of the search requests while improving the average performance. Our objective is to make it more reliable by estimating the optimal number of assumed-relevant ...

This work describes an automatic query refinement technique, which focuses on improving precision of the top ranked documents. The terms used for refinement are lexical affinities (LAs), pairs of closely related words which contain exactly one ...

One leading framework for image object mining is the bag-of-words (BOW) approach. The idea is to encode an image as a collection of visual words of the quantized local patches. Objects in the image can then be retrieved through inferring the semantic ...

Experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. Each system demonstrated improved effectiveness through the use of blind feedback, also known as pseudo-relevance ...

A usual strategy to implement CLIR (Cross-Language Information Retrieval) systems is the so-called query translation approach. The user query is translated for each language present in the multilingual collection in order to compute an independent monolingual ...

High findability of documents within a certain cut-off rank is considered an important factor in recall-oriented application domains such as patent or legal document retrieval. Findability is hindered by two aspects, namely the inherent bias favoring ...

It is well known that pseudo-relevance feedback (PRF) improves the retrieval performance of Information Retrieval (IR) systems in general. However, a recent study by Cao et al [3] has shown that a non-negligible fraction of expansion terms used by PRF ...

Although Pseudo-Relevance Feedback (PRF) is a widely used technique for enhancing average retrieval performance, it may actually hurt performance for around one-third of a given set of topics. To enhance the reliability of PRF, Flexible PRF has been ...

Query logs and pseudo-relevance feedback (PRF) offer ways in which terms to refine Web searchers' queries can be selected, offered to searchers, and used to improve search effectiveness. In this poster we present a study of these techniques that aims ...

Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becoming one of the key machineries for building search engines. Existing approaches ...

Information retrieval algorithms leverage various collection statistics to improve performance. Because these statistics are often computed on a relatively small evaluation corpus, we believe using larger, non-evaluation corpora should improve performance. ...

In an ad-hoc retrieval task, the query is usually short and the user expects to find the relevant documents in the first several result pages. We explored the possibilities of using Wikipedia's articles as an external corpus to expand ad-hoc queries. ...

This paper investigates the number of expansion terms to use in automatic query expansion by examining the behavior of eight retrieval systems participating in the NRRC Reliable Information Access Workshop. The results demonstrate that current systems ...

Experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. Each system demonstrated improved effectiveness with the use of <i>blind feedback</i>, in which the results of a ...

Blog feed search aims to identify a blog feed with a recurring interest in a given topic. In this paper, we investigate the "pseudo-relevance feedback" for blog feed search task, where its unit of relevance judgment is not based on a blog post but a ...

A (page or web) snippet is document excerpts allowing a user to understand if a document is indeed relevant without accessing it. This paper proposes an effective snippet generation method. The pseudo relevance feedback technique and text summarization ...

This paper presents a thorough analysis of the capabilities of the pseudo-relevance feedback (PRF) technique applied to distributed information retrieval (DIR). Previous studies have researched the application of PRF to improve the selection process ...