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This paper proposes an unsupervised two-stage approach to automatically extract keywords from spoken documents. In the first stage, for each candidate term we compute a topic coherence and term significance measure (TCS) based on probabilistic latent semantic analysis (PLSA) models. In the second stage, we take the
Webpage keyword is widely used in personalized search and recommendations. The accuracy of keyword is significant to the quality of search and recommendation result. Current keyword extraction methods' accuracy is not high. In order to make up for the shortage of present technology, a new keyword weight adjusting
Search engines are one of the most powerful tools in the Web world today for data retrieval and exploration. Most search engines identify the key word in the sentence or phrase or list of words given by the user and starts mining the Web for the occurrence of keyword in the Web pages. Quite often searching for the key
Along with the rapid growth of the xml data quantity on the Internet, the xml data retrieval research has attracted more and more attention. The searching algorithm based on key words is a research hotspot in this field. We present a context-based layered intersection scan algorithm (CLISA), which uses the context semantic of key words to filter large amount of redundant information, different from...
To alleviate the known semantic gap, it is necessary to integrate the two-modal parts of Web images, i.e. the low-level visual features and high-level semantic concepts (which are usually represented by keywords), for Web image retrieval. In this paper, we associate the keyword and visual features of Web images from a
interest areas coinciding with the related book categories. This paper suggests that bloggerspsila interests can be known through extracting keywords from blog entry titles and using book classification schemes. Because there were instances in which the keywords alone did not provide adequate information, the Naver (Korean
multilingual information where backend will be English database and front-end uses local languages like Hindi, Marathi or Gujrathi. Our system provides an interface to enter a keyword in local language, the keyword will be parsed, query will be formed and display the result in local language. We had developed an efficient
, interests and dislikes. If this data can be extracted and analyzed effectively, useful items, news or people can be recommended. There are high number of studies that extract keywords from texts in order to obtain such information, however, micro blogs have noisy text blocks, and hence regular text extraction algorithms fail
advent of Web mining (WM), which gives us a window in this area to allow the management of science and technology (S&T) becoming more convenient. In this paper, we use the keyword-based MA as the analysis vector doing the research on the role of WM on the TOA, and attempt to give the focus of future research in the
, trained providers. To date the corresponding role of search engine technology use and efficacy has received relatively little attention, however. This study serves as an exploratory technology assessment that explains the application of keyword effectiveness indexing (KEI) analysis in estimating the ability of commercial
performance. Apart from estimating the best path to follow, our system also expands its initial keywords by using genetic algorithm during the crawling process. To crawl Vietnamese web pages, we apply a hybrid word segmentation approach which consists of combining automata and part of speech tagging techniques for the Vietnamese
In the present world, Internet has become very familiar to everyone. In Internet, Search Engine is an efficient tool to retrieve documents related to user queries. But the documents retrieved are often large in number and most of them are unrelated to queries. The present day problem is to minimize the unrelated documents. This paper is trying to find a solution by considering a new filtering system...
Many teachers and researchers put their teaching materials on the Internet for students to read in recent years. This sort of teaching materials could be seen as static because students can only follow the learning sequence made by teachers in advance. The goal of this paper is trying to develop a tool, K-Navi toolbar, to parse and rebuild teaching materials' hypermedia structures according to the...
This paper describes a conceptual structure of application, which based on user preferences personalize news feeds. Personalize news feeds application allows for user to save time and gives him only interesting articles, news.
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