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Introduction When we search a large text collection for documents we want, we will specify some keywords and we obtain documents containing the keywords. Because the search result contains many documents, it is important to rank them. Though some methods are proposed for ranking, they did not consider positions of the keywords. As a result, such documents sometimes may be useless because the ke...

In this paper, we propose a preference framework for information retrieval in which the user and the system administrator are enabled to express preference annotations on search keywords and document elements, respectively. Our framework is flexible and allows expressing preferences such as “A is infinitely more preferred than B,” which we capture by using hyperreal numbers. Due to the widespre...

Differing from [6] this paper reduces non-linear ranking function discovering for polynomial programs to semi-algebraic system solving, and demonstrates how to apply the symbolic computation tools, DISCOVERER and QEPCAD, to some interesting examples. keywords: Program Verification, Loop Termination, Ranking Function, Polynomial Programs, Semi-Algebraic Systems, Computer Algebra, DISCOVERER, QEPCAD

This paper discusses the implementation of Support Vector Machine (SVM) based ranking metrics to compute the similarity and rank the documents based on a user query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query and ranking is done using SVM. Each query is assign...

The discovery of invariants and ranking functions plays a central role in program verification. In our previous work, we investigated invariant generation and non-linear ranking function discovering of polynomial programs by reduction to semi-algebraic systems solving. In this paper we will first summarize our results on the two topics and then show how to generalize the approach to discovering...

Ranking thousands of web documents so that they are matched in response to a user query is really a challenging task. For this purpose, search engines use different ranking mechanisms on apparently related resultant web documents to decide the order in which documents should be displayed. Existing ranking mechanisms decide on the order of a web page based on the amount and popularity of the lin...

With the increasing number of published Web services providing similar functionalities, it’s very tedious for a service consumer to make decision to select the appropriate one according to her/his needs. In this paper, we explore several probabilistic topic models: Probabilistic Latent Semantic Analysis (PLSA), Latent Dirichlet Allocation (LDA) and Correlated Topic Model (CTM) to extract latent...

Although so far, many methods for ranking fuzzy numbers have been discussed broadly, most of them contained some shortcomings, such as requirement of complicated calculations, inconsistency with human intuition and indiscrimination. The motivation of this study is to develop a model for ranking fuzzy numbers based on the lexicographical ordering which provides decision-makers with a simple and ...

Instant search is an information-retrieval in which a system finds answers to a query instantly while a user types in keywords character-by-character. Fuzzy search further improves user search experiences by finding relevant answers with keywords similar to query keywords. A main computational challenge in this the high-speed requirement, i.e., each query needs to be answered within millisecond...