The enormous growth of user-generated information of social networks has caused the need for new algorithms and methods for their classification. The Sentiment Analysis (SA) methods attempt to identify the polarity of a text, using among other resources, the ranking algorithms. One of the most popular ranking algorithms is the Okapi BM25 ranking, designed to rank documents according to their re...

In this paper I will describe the Berkeley (group 1) approach to the GeoCLEF task for CLEF 2005. The main technique we are testing is the fusion of multiple probabilistic searches against different XML components using both Logistic Regression (LR) algorithms and a version of the Okapi BM-25 algorithm. We also combine multiple translations of queries in cross-language searching. Since this is t...

We review the history of modeling score distributions, focusing on the mixture of normal-exponential by investigating the theoretical as well as the empirical evidence supporting its use. We discuss previously suggested conditions which valid binary mixture models should satisfy, such as the Recall-Fallout Convexity Hypothesis, and formulate two new hypotheses considering the component distribu...

This paper describes the updated system created by the University of Texas at Dallas for content-based medical record retrieval submitted to the TREC 2012 Medical Records Track. Our system updates our work from the previous year by building a structured query for each cohort that captures the patient’s age, gender, hospital status, and medical assertion information. Further, all keywords that e...

This paper describes the o cial runs of the Twenty-One group for TREC-7. The Twenty-One group participated in the ad-hoc and the cross-language track and made the following accomplishments: We developed a new weighting algorithm, which outperforms the popular Cornell version of BM25 on the ad-hoc collection. For the CLIR task we developed a fuzzy matching algorithm to recover from missing trans...

We present an extended technique for spoken content retrieval (SCR) that exploits the prosodic characteristics of spoken terms in order to improve retrieval effectiveness. Our method promotes the rank of speech segments containing a high number of prosodically prominent terms. Given a set of queries and examples of relevant speech segments, we train a classifier to learn differences in the pros...

In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and document terms. Our experiments show that when employed in the standard probabilistic retrieval model BM25, the additional semantic information significantly outperforms the standard term frequency, and also improves...

This paper presents our participation in medical image retrieval task of ImageCLEF 2012. Our aim is to study the effectiveness of using conceptual indexing comparing to word indexing in medical image retrieval. For this aim, we have used in the one hand the Terrier tool for textual indexing and for textual retrieval, and on another hand, the MetaMap tool for conceptual indexing and Vector model...