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The following topics are dealt with: Web intelligence; World Wide Web; Web information retrieval; information filtering; ontology engineering; semantic Web; Web mining; social networks; ubiquitous intelligence; and Web agents.
Representing meaning is a major challenge facing Web 3.0. However, it is extremely difficult to excavate the meaning of a target concept from textual data as there is no one-to-one correspondence between the textual unit in which the target concept is embedded and the conceptual content that we would like to excavate. In this paper, we propose one possible approach for addressing this challenge, by...
More and more content on the Web is generated by users. To organize this information and make it accessible via current search technology, tagging systems have gained tremendous popularity. Especially for multimedia content they allow to annotate resources with keywords (tags) which opens the door for classic text-based information retrieval. To support the user in choosing the right keywords, tag...
Visual content has become an important component of the web. In many cases, visual content is mixed with other modalities (e.g. text) that can be exploited to extract information and knowledge. This paper presents a strategy for mining multimodal visual content. The strategy encompasses two main components: a rich representation of the multimodal objects and a model for automatically annotating unannotated...
Recent years have seen a huge increase in the amount of publicly-available information relevant to drug discovery, including online databases of compound and bioassay information; scholarly publications linking compounds with genes, targets and diseases; and predictive models that can suggest new links between compounds, genes, targets and diseases. However, there is a lack of tools and methods to...
In W3C's Rule Interchange Format (RIF), F-Logic rules have received considerable attention as a major logical rule formalism, while combinations of rules with Description Logic (DL) ontologies in RIF, let alone with F-Logic rules, are far less developed. To mend this, we first present F-Logic# knowledge bases, a framework based on the semantics of the well-investigated dl-programs, that provides a...
Most of today's business processes are complex and consist of more than one party or single step procedures. In the Web, this is reflected by the existence of billions of Web sites, which may be regarded as complex processes, and on the other side only a few thousands of publicly available WSDL files that present single services. The availability of semantic descriptions of services and processes...
The explosive growth of the user-generated content on the Web has offered a rich data source for mining opinions. However, the large number of diverse review sources challenges the individual users and organizations on how to use the opinion information effectively. Therefore, automated opinion mining and summarization techniques have become increasingly important. Different from previous approaches...
In this paper, we present a Hierarchical Fuzzy Clustering algorithm which uses domain knowledge to automatically determine the number of clusters and their initial values. The algorithm is applied on a collection of web pages and the results are compared with existing algorithms in the literature.
A great share of current sentiment analysis techniques is based on special purpose lexicons providing information about the semantic orientation (e.g. positive, negative, neutral) of its entries. Due to the high labor costs of manually assembling such resources, recent work has focused on automatically inducing the polarity of given terms. We follow this line of work while focusing on the domain of...
In this paper, we propose a novel stakeholder mining mechanism for analyzing bias in news articles by comparing descriptions of stakeholders. Our mechanism is based on the presumption that interests often induce bias of news agencies. As we use the term, a ``stakeholder'' is a participant in an event described in a news article who should have some relationships with other participants in the article...
Unlike existing studies dealing with the selection of Bitmap Join Indexes for star join queries optimization, this paper presents three original features. The first one consists in addressing the problem with ant based approach that is more robust than the simple heuristic algorithms, which are usually used in the related works. The second interesting novelty resides in the metric used to prune the...
In the past, there have been many documents focusing on English reviews for sentiment analysis. These contain abundant research results which extract features and opinions, identify semantic orientation, and associate features with opinions. Although this approach has performed well for English reviews, it is not as successful with Chinese reviews. In this paper, we aim to develop a sentiment analysis...
Opinion mining is of great significance in the analysis of user generated content. While there is some progress in supervised classification of opinion, the unsupervised learning of product features has drawn less attention. Unlike previous approaches based on basic syntactic pattern, our product feature mining utilizes syntactic dependency knowledge in a novel way by discriminating nominal and non-nominal...
Identifying cohesive subgroups in networks, also known as clustering is an active area of research in link mining with many practical applications. However, most of the early work in this area has focused on partitioning a single network or a bipartite graph into clusters/communities. This paper presents a framework that simultaneously clusters nodes from multiple related networks and learns the correspondences...
Today's world is characterized by the multiplicity of interconnections through many types of links between the people, that is why mining social networks appears to be an important topic. Extracting information from social networks becomes a challenging problem, particularly in the case of the discovery of community structures. Mining bibliographical data can be useful to find communities of researchers...
An increasing number of people are socializing within online networks. By means of interaction, network members influence one another's opinion. For companies, it is important to know how opinions spread throughout networks in order to be able to take appropriate marketing actions. A new approach is presented which simulates the spread of opinions within online social networks. The principles of opinion...
Reuse is an important mechanism for improving the efficiency of software development. For Internet-scale software produced through service composition, the simple reuse granularity at service is often inefficient due to the large number of available services. This paper proposes a novel architecture which enables efficient reuse of process fragments. In the proposed architecture, services are organized...
Web 2.0 provided internet users with a dynamic medium, where information is updated continuously and anyone can participate. Though preliminary analysis exists, there is still little understanding on what exactly stimulates users to actively participate, create and share content in online communities. In this paper we present a methodology that aspires to identify and analyze those events that trigger...
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