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This paper presents a method of using wearable accelerometers and microphones to detect instances of ad-hoc physical collaborations between members of a group. 4 people are instructed to construct a large video wall and must cooperate to complete the task. The task is loosely structured with minimal outside assistance to better reflect the ad-hoc nature of many real world construction scenarios. Audio...
Recommendation technique is a personalized search used to assist a user access information/services that are related to his preferences and interests, or to the preferences and interests of similar users. The main challenge of personalized Information Retrieval is the modeling and the integration of user profiles. In this paper, we propose a generic model of user profiles based on the search history...
Social networks and location based social networks have many active users who provide various kind of data, such as where they have been, who their friends are, which items they like more, when they go to a venue. Location, social network and temporal information provided by them can be used by recommendation systems to give more accurate suggestions. Also, recommendation systems can provide dynamic...
Collaborative filtering can predict an active user's interests for unrated items based on his observed ratings, and the issue of concept drift exists in most of recommender systems. Aiming at the issue of concept drift, a time-enhanced collaborative filtering approach is proposed in this work, in which a time weight is introduced into the framework of collaborative filtering. As the experimental results...
We conducted a user study evaluating two preference elicitation approaches for collaborative filtering recommender systems: a basic KNN algorithm and a context aware algorithm. Using the technology acceptance model (TAM) as theoretical model, we considered different factors affecting the perceived usefulness, perceived ease of use and attitude towards using the recommender system. We found that the...
This article addresses trust in computer systems as a social phenomenon, which depends on the type of relationship that is established through the computer, or with other individuals. It starts by theoretically contextualizing trust, and then situates trust in the field of computer science. Then, describes the proposed model, which builds on what one perceives to be trustworthy and is influenced by...
The success of traditional learning is based on the individual use of learning tools, depending on the learners' personality. But modern eLearning is disregarding this major fact. By using learning analytics, this paper examines the correlation between personality traits of the user and preferred learning tools in an eLearning scenario. The investigation is based on a field study with 992 participants...
Current research environments are witnessing high enormities of presentations occurring in different sessions at academic conferences. This situation makes it difficult for researchers (especially juniors) to attend the right presentation session(s) for effective collaboration. In this paper, we propose an innovative venue recommendation algorithm to enhance smart conference participation. Our proposed...
With popular microblogging services like Twitter, users are able to online share their real-time feelings in a more convenient way. The user generated data in Twitter is thus regarded as a resource providing individuals’ spontaneous emotional information, and has attracted much attention of researchers. Prior work has measured the emotional expressions in users' tweets and then performed various analysis...
In this study, a computerized collaborative concept-mapping approach is proposed. To evaluate the effectiveness of this innovative approach, a learning activity has been conducted on an elementary school natural science course. Two hundred and twenty fifth graders from seven classes were divided into an experimental group, in which the students learned with the proposed approach, and a control group,...
Previous studies have established the significant relationships between knowledge management practices (KMPs) and firm capabilities development (FCD). These relationships, however, could possibly be moderated by knowledge expropriation hazard (KEH) arising from the opportunism of human beings. Based on knowledge management and strategic alliance research, the main objective of this paper is to empirically...
In this demo we present DiRec, a plug-in that allows Collaborative Filtering (CF) Recommender systems to diversify the recommendations that they present to users. DiRec estimates items diversity by comparing the rankings that different users gave to the items, thereby enabling diversification even in common scenarios where no semantic information on the items is available. Items are clustered based...
In this paper, we report the findings of an empirical investigation into decision making processes (DMPes) in distributed teams. We conducted the study in a Fortune 500 organization with a total of sixteen respondents who participated in an hour-long interview. Our analysis of the DMP reported by our respondents suggests that there is a strong organizational culture that supersedes local and individual...
Traditional recommendation approaches do not consider the changes of user preferences according to context. As a result, these approaches consider the userpsilas overall preferences, although the user preferences on items varies according to his/her context. However, in our context-aware approach, we take into account not only user preferences, but also context information. Our approach can be easily...
With rapid development of computer networks, users need a new solution for network security management, aiming at integration. This paper focuses on context-aware alert analysis, which is one of its key functionalities. A practical and efficient approach to guarantee unified representation of context information, background knowledge and attack knowledge for security alerts is still lacking these...
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