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Web automation programs offer a means for users to enhance the usability of the web. These programs can be published on a wiki or other repository, thereby making them available for use by other users. However, in addition to programs of broad usefulness to the community at large, these repositories also contain many programs that are unreliable or highly specialized to the needs of very small sub-...
Individuals are turning increasingly toward web-based information sources as input for complex decisions. Gathering and evaluating decision criteria in an online context is enticing because of information availability and increased control over the process, but how do these factors impact performance? This study shows how an interaction effect between Social Comparison and Social Facilitation predicts...
Zillow is a web-based, leading real-estate information service in the US. We studied user-contributed facts in a sample of Zillow records. User-contributed information seems to improve the completeness and the level of detail of the information on Zillow.com. However, the accuracy of user-contributed facts may not be high. An investigation of the sources of error revealed several weaknesses, including...
As one of the emerging Web 2.0 activities, tagging becomes a popular approach to manage personal media data, such as photo albums. A dilemma in tagging behavior is the users' manual efforts and the tagging accuracy: exhaustively tagging all photos in an album is labor-intensive and time-consuming, and simply entering tags for the whole album leads to unsatisfying results. In this paper, we propose...
To take advantage of the Internet - vast but complicated information resources, Recommendation systems help users find out information they need by providing them personalized suggestions. This research area is receiving more and more attention from researchers and used in some famous websites like EBay, Amazon, etc. In this paper, we proposed a Recommendation System for Vietnamese electronic newspaper...
When we are dealing with community structure detecting in the blogosphere, we have come to face some obstacles. The data in a blog may be updated frequently by its owner, making the whole blogosphere become very large during a short period of time. It can be very expensive to deal with such huge amount of data using those traditional methods. Meanwhile, few blogs in the blogosphere can be identified...
Electronic Commerce has offered a convenient way for people to go shopping on the Internet. However, it is difficult for Internet customers to select a valuable item from the great number of various products available on line. When we use a keyword and search in a EC website, the ranking algorithm of products is usually based on statistics or simply the shop manager's preference, which does not fully...
This paper explores online learning and batch algorithms for detecting malicious Web sites (those involved in criminal scams) using lexical and host-based features of the associated URLs. A data set has been built including malicious and benign URLs, and data mining system Weka has been used as an aid to classify the existent URLs and new coming URLs and evaluate the classification algorithms. A real-time...
This paper proposes an algorithm of personalized blog information retrieval based on user's interest model. First of all, it discusses the system architecture of personalized blog information retrieval. Next it studies the identification module of blog web page. Then it focuses the document feature representation and the algorithm flow of blog document similarity based on the vector space model. And...
After a brief analysis to the information spreading mode under internet-based micro-blog platform, it quickly classifies and audits the related mirco-blog content in the spreading process in this paper. Then, by analyzing the sender's mood tendency to some specific topics in the content of micro-blog message, it proposes a content audit model under the micro-blog service platform. Furthermore, by...
This paper addresses clustering of blog users and posts in blogosphere. First, we model blogosphere as a bipartite graph where blog users and posts correspond to nodes of two types and actions on posts performed by blog users corresponds to links. Next, for clustering in blogosphere, we employ LinkClus, a link-based algorithm that finds clusters of nodes in a network effectively and efficiently. For...
In the blogosphere, the amount of digital content is expanding and for search engines, new challenges have been imposed. Due to the changing information need, automatic methods are needed to support blog search users to filter information by different facets. In our work, we aim to support blog search with genre and facet information. Since we focus on the news genre, our approach is to classify blogs...
In a variety of domains, the amount of information grows rapidly; new sources and types of information are proliferating. In recent years, the world-wide web information has been growing at a dramatic pace and might have become the most important information source for most people. In daily life, when people encounter some problems, they tend to retrieve the information from the Web search engines...
Really Simple Syndication(RSS) has been widely used in our daily lives, but RSS doesn't always collect interesting articles, user has to sift through every subscription for articles they like. The ranking of unread RSS articles has the potential power to release user from this heavy burden. Although user preferences can be learned from explicit feedbacks such as rating or tagging, implicit feedback...
Along with the rapid popularity of the Internet, crime information on the web is becoming increasingly rampant, and the majority of them are in the form of text. Because a lot of crime information in documents is described through events, event-based semantic technology can be used to study the patterns and trends of web-oriented crimes. In our research project on cyber crime mining, we construct...
With the rapid growth of the World Wide Web (WWW), finding useful information from the Internet has become a critical issue. Web recommender systems help users make decisions in this complex information space where the volume of information available to them is huge. Recently, a number of web page recommender systems have been developed to anticipate the information needs of on-line users and provide...
Due to the complexity of topical opinion retrieval systems, standard measures, such as MAP or precision, do not fully succeed in assessing their performances. In this paper we introduce an evaluation framework based on artificially defined opinion classifiers. Using a Monte Carlo sampling, we perturb a relevance ranking by the outcomes of these classifiers and analyse how the opinion retrieval performance...
Real time application was required many types of industrial controllers, factory machines since 20-century. It is also utilizing many types of real time controllers for vehicle such as train, automobile and so on. On the other hand, Web services that are using Internet are required short latency system. When the accesses are increased, services of quality are so important factors to achieve their...
Accelerated growth of the Internet has enabled users worldwide to share their feelings and experiences. User-generated content (UGC) websites are the most abundant sources of user reviews. Accurately identifying sentiment phrases is essential to understand the expressed opinions in user reviews. To achieve this, part-of-speech (POS) patterns of phrases are useful. However, previous studies for Chinese...
This paper presents a method of related subject of Tibetan web integrating content evaluation and link analysis. The analysis of related subject of Tibetan web is the most important part of the special Tibetan Search. It guide web crawler download pages accurate and efficient. The content evaluation of this method extends the VSM based on keyword, it consider that the keywords in the page have different...
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