Network structure often contains information that can be useful for ranking algorithms. We incorporate network structure by formulating ranking as marginal inference in a Markov random field (MRF). Though inference is generally NP-hard, we apply a recently-developed polynomial-time approximation scheme (PTAS) to infer Bethe pseudomarginals. As a case study, we investigate the problem of ranking...

Semantic ranking models go beyond keyword matching to score documents based on closeness in meaning to the query. The use of semantic ranking in Web search has been limited due to the high cost of these models. To address this issue, we have designed and implemented a new Web-scale ranking system that enables us to integrate semantic ranking techniques into a commercial search engine. We have e...

introduction: today, huge quantity of medical journals with indescribable quality, have confused health researchers while choosing a suitable journal to publish their scientific results. it seems that quality measuring criteria of journals could have solved this problem to some extent. in this study, we studied quality of journals of obstetrics and gynecology field indexed in the valid database...

Abstract: Single feature is inefficient to describe content of an image, which is a shortcoming in traditional image retrieval task. We know that one image can be described by different features. Multi-feature fusion ranking can be utilized to improve the ranking list of query. In this paper, we first analyze graph structure and multi-feature fusion re-ranking from manifold aspect. Then, Three ...

Ranking module is an important component of search process which sorts through relevant pages. Since collection of Web pages has additional information inherent in the hyperlink structure of the Web, it can be represented as link score and then combined with the usual information retrieval techniques of content score. In this paper we report our studies about ranking score of Web pages combined...

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learn the ranking scores from data points plays an important role. Up to new, these two methods have always been used individually, assuming that data coding and ranking are two independent and irrelev...

In most ranking systems for information retrieval, there are multiple signals that need to be combined to generate a single score for ranking a result. In this work we consider how the output score of various ranking systems can be combined to rank the TREC 2003 and 2004 benchmark datasets. Not surprisingly, we find that the performance of a combined system is able to achieve significantly bett...

Answer ranking is critical to a QA (Question Answering) system because it determines the final system performance. In this paper, we explore the behavior of shallow ranking features under different conditions. The features are easy to implement and are also suitable when complex NLP techniques or resources are not available for monolingual or cross-lingual tasks. We analyze six shallow ranking ...