Keyword extraction of scientific articles is beneficial for retrieving scientific articles of a certain topic and grasping the trend of academic development. For the task of keyword extraction for Chinese scientific articles, we adopt the framework of selecting keyword candidates by Document Frequency Accessor Variety(DF-AV) and running TextRank algorithm on a phrase network. To improve domain ...

In this paper, a novel keyword propagation method is proposed for image retrieval based on a recently developed manifold-ranking algorithm. In contrast to existing methods which train a binary classifier for each keyword, our keyword model is constructed in a straightforward manner by exploring the relationship among all images in the feature space in the learning stage. In relevance feedback, ...

in any political system, recognition of constitutional keywords is an important pathway for understanding constitutional system desirably. the recognition matters increasingly, when a keyword is rooted in constitutional system&aposs; ideological bases and its underlying political theory. ummah, a term with religious and islamic theme, has come from religious literature into the constitution of ...

Keyword spotting is a very forward-looking and promising branch of speech recognition. This paper presents a HMM-based keyword spotting system, which works with a new algorithm. The first discussion topic is the description of the search algorithm, that needs no representation of the non-keyword parts of the speech signal. For this purpose, the computation of the HMM scores and the Viterbi algo...

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

Keyword search in XML documents has recently gained a lot of research attention. Given a keyword query, existing approaches first compute the lowest common ancestors (LCAs) or their variants of XML elements that contain the input keywords, and then identify the subtrees rooted at the LCAs as the answer. In this the paper we study how to use the rich structural relationships embedded in XML docu...

We previously proposed a fast spoken term detection method that uses a suffix array data structure for searching large-scale speech documents. The method reduces search time via techniques such as keyword division and iterative lengthening search. In this paper, we propose a statistical method of assigning different threshold values to sub-keywords to further accelerate search. Specifically, th...

In this paper we consider the problem of efficiently producing results for full-text keyword search queries over XML documents. We describe full-text search query semantics and propose a method for efficient evaluation of keyword search queries with these semantics suitable for native XML databases. Method uses inverted file index which may be efficiently updated when a part of some XML documen...