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Identifying real-world business communities, e.g., Energy, finance, defense, in Internet traffic is a challenging problem but would be valuable for the construction of better in-trusion detection techniques, for example. Seed-based community detection identifies a community in a graph by iteratively adding the 'closest' vertices to an initial set of seed-vertices which are known to belong to the community...
In cross-organizational transactions, resolving the responsible agent is always an issue. This is usually done using local address books, directories and similar information sources. The redundant maintenance of such external organizational information causes many discrepancies between the organizational models. This paper describes an approach to overcome this problem. It shows how organizational...
This contribution introduces a failover strategy for agent lookup in workflows. It is based on an organizational model and relations between different model elements. The algorithms that evaluate the organizational model prioritize local before global knowledge. Local knowledge is better suited to handle exceptions than global rules. The algorithms are able to find the correct agents even in unplanned...
This paper describes our attempt to extract various relations between super ordinate concepts from terabytes of Web corpus for human-like speculation of the meaning of unknown terms. In order to discover various conceptualized relations, we focus on Web-scale text corpora and introduce a simple string-matching method to process them. To derive relations between concepts, our method first extracts...
Sentence similarity methods are used to assess the degree of likelihood between phrases. Many natural language applications such as text summarization, information retrieval, text categorization, and machine translation employ measures of sentence similarity. The existing approaches for this problem represent sentences as vectors of bag of words or the syntactic information of the words in the phrase...
In this paper, methods for ranking coordinate terms and hypernyms of a given query according to their appropriateness are proposed. Although previous studies have proposed methods for discovering coordinate terms or hypernyms of a query, they focused on only discovering such terms and evaluating discovered terms based on a binary evaluation: appropriate or inappropriate. Unlike these studies, we rank...
This paper discusses the recommender models and methods for crowd sourcing platforms. These models are based on modern methods of data analysis of object-attribute data, such as Formal Concept Analysis and biclustering. In particular, the paper is focused on the solution of two tasks - idea and antagonists recommendation - on the example of crowd sourcing platform Witology.
Negotiation is a fundamental mechanism in multi-agent systems since it allows self-interested agents to come to mutual agreements and to distribute resources efficiently and effectively. However, in competitive situations, the agents need to negotiate repeatedly with one another, thus developing mechanisms that are effective over repeated interactions is a key challenge. At present, few research work...
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