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Recently, heterogeneous information network(HIN) analysis has attracted a lot of attentions. One of the HIN application is recommendation. Due to HIN containing multiple different objects and links and rich semantic meanings, it is promising to generate better recommendation. Previous studies on movie recommendation have combined the single implicit feedback information with heterogeneous information...
It is very crucial for news aggregator websites which are recent in the market to actively engage its existing users. A recommendation system would help to tackle such a problem. However, due to the lack of sufficient amount of data, most of the state-of-the-art methods perform poorly in terms of recommending relevant news items to the users. In this paper, we propose a novel approach for Item-based...
Federation is generally used to denote collaboration between IT systems in different administrative domains to achieve common goals. Different administrative domains are typically distinct and loosely coupled by definition. While domains may have some degree of self-awareness, their awareness of other domains may be weak or non-existent. Hence, there is a fundamental challenge concerning how to build...
Different from current researches on Flickr group recommendation approaches that recommend groups to either users or images, this work proposes a unified framework that recommends groups to both users and images. Four types of entities in the Flickr system (users, tags, images, and groups) are integrated into a tetradic model, and then we uses tetradic decomposition to discover the latent semantic...
Real-time collaborative programming allows programmers to concurrently edit shared source code over communication networks. To support semantic conflict prevention, prior work has proposed a bask dependency-based automatic locking (DAL) approach to automatically grant locks on source code regions with dependency relationships, under the assumptions that there exists no locking-scope overlapping among...
In order to generate effective results, it is essential for a recommender system to model the information about the user interests (user profiles). A profile usually contains preferences that reflect the recommendation technique, so collaborative systems represent a user with the ratings given to items, while content-based approaches assign a score to semantic/text-based features of the evaluated...
Sensemaking is a process of finding meaning from information that often involves activities such as information foraging and hypothesis generation. It can be valuable to maintain a history of the data and reasoning involved. This history, commonly known as provenance information, can be a resource for "reflection-in-action"' during analysis, supporting collaboration between analysts, and...
Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform...
In this paper we examine the possibilities for analyzing the behavior of library users. We point out that the softwares that we can use cannot fulfill library requirements. There are many data given for on-line searches in library systems hidden from the analyzers. After examining the possibilities and some log files produced by the library systems, we propose how log files could give more usable...
Dealing with user incidents, questions and problems are important tasks during the maintenance of the software. It is specially important for service providers, which must provide the users with a quick and reliable answer. Many times the incident has been previously solved for other users. In these cases, an appropriate knowledge management strategy could help to improve response times as well as...
Social content-sharing networks allow users to share content annotations. Although convergence and consistency in semantic annotation (tags) has been well-studied, less effort has been devoted to studying evaluative annotations (ratings and reviews) with respect to user characteristics and user-item relationships. In this paper, we first identify trends in both item scores and in the ways in which...
The workshop provides an interdisciplinary forum for researchers and practitioners to present and discuss their ideas related to the usage of semantic technologies for information-integrated collaboration. We address a wide array of questions concerning two fundamental design problems arising when realizing integrated collaboration solutions, namely semantic inaccessibility and logical disconnectedness...
In a dynamic and heterogeneous world as the Web, the need often arises to update XML data, as well as their structures, to adhere to new domain requirements. Updates may break compliance of data to schemas, and updates at schema level may in addition require to adapt associated documents to the new schema. Moreover, emerging application contexts in which updates come from different sources, such as...
Satisfaction is a key indicator of system success, and so has been the subject of much IS research. The nostalgia effect, whereby individuals feel satisfied or dissatisfied when thinking about past goal attainment or failure, has been observed to influence analysts' decisions with respect to ongoing systems development. The Yield Shift Theory (YST) of Satisfaction offers an explanation for the nostalgia...
Social tagging systems such as Facebook, YouTube, del.icio.us, Flickr become popular recent years and have achieved widespread success. State-of-art user modeling approaches in tagging systems usually use a vector of weighted tags. Unfortunately, typical user modeling methods using a vector of weighted tags which are based on personal view only and ignore the social view, have some inherent drawbacks...
The development and maintenance of ontologies more often than not requires tools for their collaborative authoring. The existing tools come with a significant overhead for their installation and operation. This overhead is acceptable for large ontologies with hundreds and thousands of classes; but in some communities and projects e.g. in the eHumanites it poses a major adoption barrier. This paper...
In general, content-based recommender systems use a keyword vector to locate recommendations. However, this method does not consider relations of each keyword and it is also inscrutable to users, who may have a hard time determining which words in their profiles are important and which may be skewing their results to irrelevant recommendations. In contrast, the method proposed in this paper automatically...
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