Description: Abstract: This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Previous work on this problem has focused mainly on either large documents (e.g. text classification, information retrieval) or individual words (e.g. synonymy tests). Given that a large fraction of the information available today, on the Web and elsewhere, consists of short text snippets (e.g. abstracts of scientific documents, image captions, product descriptions), in this paper the authors focus on measuring the semantic similarity of short texts. Through experiments performed on a paraphrase data set, the authors show that the semantic similarity method out-performs methods based on simple lexical matching, resulting in up to 13% error rate reduction with respect to the traditional vector-based similarity metric.

Description: This paper discusses automatic generating of back-of-the-book indexes. Abstract: The automatic generation of back-of-the-book indexes seems to be out of sight of the Information Retrieval and Natural Language Processing communities, although the increasingly large number of books available in electronic format, as well as recent advances in key-phrase extraction, should motivate an increased interest in this topic. In this paper, the authors describe the background relevant to the process of creating back-of-the-book indexes, namely (1) a short overview of the origin and structure of back-of-the-book indexes, and (2) the correspondence that can be established between techniques for automatic index construction and keyphrase extraction. Since the development of any automatic system requires in the first place an evaluation testbed, the authors describe their work in building a gold standard collection of books and indexes, and the authors present several metrics that can be used for the evaluation of automatically generated indexes against the gold standard. Finally, the authors investigate the properties of the gold standard index, such as index size, length of index entries, and upper bounds on coverage as indicated by the presence of index entries in the document.

Description: This paper discusses cross-lingual semantic relatedness using encyclopedic knowledge. Abstract: In this paper, we address the task of cross-lingual semantic relatedness. We introduce a method that relies on the information extracted from Wikipedia, by exploiting the interlanguage links available between Wikipedia versions in multiple languages. Through experiments performed on several language pairs, we show that the method performs well, with a performance comparable to monolingual measures of relatedness.

Description: In this paper, the authors evaluate the extent to which human-written book summaries can be obtained through cut-and-paste operations from the original book. The authors analyze the effect of the parameters involved in the decomposition algorithm, and highlight the distinctions in coverage obtained for different summary types.

Description: This paper discusses dynamic agent population in agent-based distance vector routing. Abstract: The Intelligent mobile agent paradigm can be applied to a wide variety of intrinsically parallel and distributed applications. Network routing is one such application that can be mapped to an agent-based approach. The performance of any agent-based system will depend on its agent population. Although a lot of research has been conducted on agent-based systems, little consideration has been given to the importance of agent population in dynamic networks. A large number of constituent agents can increase the resource overhead of the system, thereby impeding the overall performance of the network. Hence, it is imperative to find the optimal number of agents in the system that would maximize the efficiency of the agent-based mechanism in the network. This optimal value cannot be determined manually, thereby emphasizing the need for an adaptive approach that manipulates the number of agents in the system based on its resource availability. This paper discusses an agent-based approach to Distance Vector Routing, referred as Agent-based Distance Vector Routing and also describes an adaptive approach controlling the number of agents in the network using pheromones and discusses their limitations.