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fields and provides to the researchers the application form best matched to the researcher's current research field. We have developed recommendation system of Grant-in-Aid system for researchers by using JSPS (Japan Society for the Promotion of Science) keywords. The system can determine some rules associated between the
based spam topic detection strategy through keyword extraction. In particular, spam topic is detected by using the topic model of multiple features with the keywords of clues, which integrate the corresponding feature of News, BBS and Blog. We get the min cost of 0.282 through TDT4 evaluating corpus and the satisfaction of
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
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
This paper proposes a mutual detection mechanism between spam blogs and keywords for filtering spam blogs from updated blog data. Spam blogs are problematic in extracting useful marketing information from the blogosphere; they often appear to be rich sources of information based on individual opinion and social
keywords from the Web pages. The system first identifies the section of the Web page that contains the multimedia file to be extracted and then extracts it by using clustering techniques and other tools of statistical origin. Experimental results on real-world image sharing Web sites are presented and discussed in this paper
Web pages for search engine. First we describe a scheme based on semantic keywords combined with sentence overlapping, and then show an implemented prototype, with the experimental results that suggest the prototype work well under a proper setting.
Content-based phishing detection extracts keywords from a target Web page, uses these keywords to retrieve the corresponding legitimate site, and detects phishing when the domain of the target page does not match that of the retrieved site. It often misidentifies a legitimate target site as a phishing site, however
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
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
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
The goal of this paper is to cross-lingually analyze multilingual blogs collected with a topic keyword. The framework of collecting multilingual blogs with a topic keyword is designed as the blog feed retrieval procedure. Multilingual queries for retrieving blog feeds are created from Wikipedia entries. Finally, we
needed to search and find relevant information. For tabular structures embedded in HTML documents, typical keyword or link-analysis based search fails. The next phase envisioned for the WWW is automatic ad-hoc interaction between intelligent agents, web services, databases and semantic web enabled applications. A large
the crawled Web pages in to repositories. At first, the keywords are extracted from the crawled pages and the similarity score between two pages is calculated based on the extracted keywords. The documents having similarity scores greater than a threshold value are considered as near duplicates. The detection has
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
queries, reverse queries, Webpage title and keyword phrases are combined with the cluster centers to attain high-quality expansion terms for new queries. We also propose a new terminology extraction method through Baidu Baike. It can identify and extract the terminology phrase based on the manual edited dictionary online.
designed and implemented to resolve the problem of crossing language queries and retrieving images processes. It can greatly reduce lot of time and effort for the search. The experiments on diverse queries on Yahoo images search have shown that the proposed scheme can improve the images results for non-English keyword
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
Writing and browsing education blogs has become one of the important methods of e-learning. Learners can search the interesting resources from these education blogs. However, the traditional blog search only provides keyword-based matching, lacking automatic extraction of learner interests and further interest-related
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