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Keyword extraction is an important application in the area of information technology. Automatic keyword extraction can help people know what is the article primarily talking about without reading the long passage carefully. This paper mainly introduced a keyword extraction algorithm using pagerank on Synonym. Firstly
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs.Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
The traditional layout of news websites, the combination of classified hierarchical browsing, headline recommendation and keyword-based search, has been used for many years. The keyword-based search is considered to be the most powerful tool for news browsing and retrieval. Unfortunately, the keyword-based query
Social media keeps growing and providing us with rich sources of information to understand our everyday lives, customs, and culture in the form of periodic topics. This paper proposes a method of detecting periodic topics based on autocorrelation using the time series of the document frequencies of keywords. To deal
popularity and co-occurrence data. We describe a prototype that leverages the Wikipedia category structure to allow a user to semantically navigate pages from the Delicious social bookmarking service. In our system a user can perform an ordinary keyword search and browse relevant pages but is also given the ability to broaden
interchangeable module which uses 2-Way SMS for allowing the interchange of messages, traffic query and result, between mobile device and the system. 2) The data retrieving module which feeds the really simple syndication (RSS) document from NECTEC real-time traffic report Website for traffic information retrieval. 3) The keyword
In this paper, reclassification for the current classification through K-means would be implemented based on the feedback of Web usage mining in order to improve the accuracy of news recommendation and convergence of classification. It could extract most relative keywords and eliminate the disturbance of multi-vocal
agent that targets a particular topic and visits and gathers only relevant web pages. In this dissertation I had worked on design and working of web crawler that can be used for copyright infringement. We will take one seed URL as input and search with a keyword, the searching result is based on keyword and it will fetch
In the past few years, there has been an exponential increase in the amount of information available on the World Wide Web. This plethora of information can be extremely beneficial for users. However, the amount of human intervention that is currently required for this is inconvenient. Information extraction (IE) systems try to solve this problem by making the task as automatic as possible. Most of...
Topic-oriented search engine (topic-search) is a new IR service which provides compounded types of information with certain user queried topic in one page. It firstly categorizes user query into a certain domain, and then organizes several types of information based on the query keywords into a magazine-style topic
their personal file system by leveraging semantic relationships available on the Web. More specifically, JabberWocky is using keyword/resource associations of social bookmarking web sites as a basis for recommending keywords for files. We chose social bookmarking web sites because of their popularity and because the
videos, we can only use a title. If there are tags - significant keywords of that multimedia, we can use tag information to search. Tag is a keyword of text, blog post, or multimedia. Users have already recognized about the value and importance of tags but only a few users are using tags. They might be annoying to add tags
A new method to compute the similarity of two blog posts is proposed in this paper. This method mainly has two parts including keywords extraction and semantic similarity measurement. During keywords extraction part, the method utilizes particular post features to extract keywords from one blog post with the aim to
weight of every sentence in a topic block is calculated in view of query keywords. Finally, several important sentences are dynamically extracted to compose the digest according to expected compression ratio with the improved maximal marginal relevance method, which can remove redundant information in summary. The
This paper describes a new approach of enhancing textual document search and retrieval. The approach tries to take advantage of structured query languages in search and retrieval. For this purpose the semantic model of the document is created. The semantic model of the document is an ontology-like structured semantic annotation of the document that can support structured querying. This paper discusses...
relations and bi relation patterns; TCMW-MODEL is used for acquiring the sets of the domain keywords in the traditional Chinese medicine. Our experimental results show the precision/recall of data extraction using this system is as good as those from the templates based on structured information extraction. The domain experts
automatically constructs a navigational structure for the WWW to help information finding. A self-organizing map is constructed to train the Web pages and obtain two feature maps, which reveal the relationships among Web pages and thematic keywords respectively. We then use these maps to develop a structure that may assist the
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