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Collection and analysis of information about network public opinion has currently become an effective means to get people thinking and recommendations by the government departments. In this paper, we presents a method of BBS(Bulletin Board System) hot topic analysis based on multiple keywords combination, this method
Automatic assessment of learners responses has gained wider acceptance and popularity in recent times. Due to associated complexities of free text evaluation, the trend has gradually shifted towards close ended question which have their limitations. The current work proposes a rough set based strategy to augment
In this paper, we present a keyword extraction methodology from handwritten Chinese document image based on matching and voting of the local topological structure. In the process, a handwritten keyword image is used as template, from which the local topological structure features of each character pixel are extracted
explicitly specify return information, our system will automatically analyze and choose appropriate return nodes by inferring from user keywords. Second, to return a meaningful result, we investigate the problem of the return information in the LCA and the proximity search approaches. To this end, we introduce the Lowest
The analysis of the vast storehouse of email content accumulated or produced by individual users has received relatively little attention other than for specific tasks such as relationship. Current email analysis in standard client applications consists of keyword based matching techniques for relationship of email
and privacy. As a result, owners of sensitive information may be skeptical in purchasing such services, given the risks associated with the unauthorized access to their data. To this end, searchable encryption is a family of cryptographic protocols that facilitate private keyword searches directly on encrypted data
, social networks such as Facebook, and data from news stations. Such geo-textual data allows to immediately detect and react to new and emerging trends. A trend is a set of keywords associated with a time interval where the frequency of these keywords is increased significantly. In this paper, we investigate the
of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works focused only to retrieve separate tweets or those sharing same hash tags, but, it is not powerful enough if the goal of the search is to retrieve relevant tweets based on content. In
because they are poorly indexed due to their sensitive content, these pages are hard-to-find with traditional search engines. In this article, we describe a new Web source discovery system called DOWSER (Discovery Of Web Sources Evaluating Relevance). The goal of this system is to provide users with new sources of
server. Since most email is stored in plaintext, a compromise of the server implies the loss of confidentiality and integrity of the email stored therein. Although users could employ an end-to-end encryption scheme (e.g., PGP), such measures are not widely adopted, require action on the sender side, only provide partial
Although the problem of spam detection in email is well understood and has been extensively researched, a significant portion of emails today are spam. A most widely used method to detect spam involves content filtering, where the spam detector scans the received email for keywords. However, the same approach cannot
traffic. The simple way to identify Webmail traffic is mapping source or destination IP address with URLs of Webmail providers (e.g. Hotmail, Yahoo!, and Gmail), is neither flexible nor accurate. The URL mapping technique cannot detect some related Webmail traffic such as advertising banners, pictures, and news, which are
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