This study evaluates the robustness of established computational indices used to assess text relatedness in user-language. The original User-Language Paraphrase Corpus (ULPC) was compared to a corrected version, in which each paraphrase was corrected for typographical and grammatical errors. Error correction significantly affected values for each of five computational indices, indicating greater similarity of the target sentence to the corrected paraphrase than to the original paraphrase. Moreover, misspelled target words accounted for a large proportion of the differences. This study also evaluated potential effects on correlations between computational indices and human ratings of paraphrases. The corrections did not yield assessments that were any more or less comparable to trained human raters than were the original paraphrases containing typographical or grammatical errors. The results suggest that although correcting for errors may optimize certain computational indices, the corrections are not necessary for comparing the indices to expert ratings.

Two sentences are paraphrases if their meanings are equivalent but their words and syntax are different. Paraphrasing can be used to aid comprehension, stimulate prior knowledge, and assist in writing skills development. While automated paraphrase assessment is both common-place and useful, research has centered solely on artificial, edited paraphrases and has used only binary dimensions (i.e., is or is-not a paraphrase). In this study, we use 1998 natural paraphrases generated by high school students that have been assessed along 10 dimensions of paraphrase (e.g., semantic completeness). This study investigates the components of paraphrase quality emerging from these dimensions, and examines whether computational approaches (e.g. LSA, MED) can simulate those human evaluations. The results suggest that semantic and syntactic evaluations are the primary components of paraphrase quality, and that computationally light systems such as LSA (semantics) and MED (syntax) present promising approaches to simulating human evaluations of paraphrases.

Using the already validated Coh-Metrix tool, this study examines whether there are significant linguistic and discourse differences between biomedical abstracts for American and Korean English. Also, the current study accounts for variation among journals’ countries of origin, distinguishing between biomedical journals published in the United States from biomedical journals published in South Korea. The significance of these studies regards the growing number of second language (L2) biomedical researchers attempting to publish their research in national and international English-language journals, but who find themselves locked out of the discussion because of differences in linguistic and discourse conventions. The present study aims to provide a more thorough and quantitative understanding of the prototypical linguistic components in biomedical rhetoric, and to suggest how word-, sentence-, and discourse-level structures can be researched, taught, and developed into materials. This improved understanding is expected to provide a powerful apparatus for the promotion of L2 English writers in the biomedical field.

In this paper, we propose a universal solution to web search and web browsing on handheld devices for visually impaired people. For this purpose, we propose (1) to automatically cluster web page results and (2) to summarize all the information in web pages so that speech-to-speech interaction is used efficiently to access information.

A general practice in the research of metaphor has been to investigate its behavior and function in different contexts. This current study aims to investigate the notion that verbs possess a metaphor-making potential, this being an initiatory context-free experiment with metaphor. The goal of this paper is to carry out an in-depth case study of a group of English core verbs using WordNet and SUMO ontology. In order to operationalize the measurement of an English verb’s metaphor making potential, a new algorithm has been developed, and a program made to realize the computation. At last, it has been observed that higher frequency verbs generally possess greater metaphor making potential; while a verb’s metaphor making potential on the other hand is also strongly influenced by its functional category.

This paper proposes a new approach to improve domain independent heuristic state space search planners for classical planning by tuning the search heuristics using macro actions of length two extracted from sample plans. This idea is implemented in the planner AltAlt and the new planner Macro-AltAlt is tested on the domains introduced for the learning track of the International Planning Competition (IPC-2008). The performance of Macro-AltAlt measured by the length of the plan found and the number of states explored to find the plan is compared with that of AltAlt.

A problem of path planning for multiple robots is addressed in this paper. A specific case of the problem with so called theta-like environment is studied. This case of the problem represent structurally the simplest solvable case and an eventual solving method for this case can be used as a building block for more general solving procedures. We propose a solving method for multi-robot path planning in theta-like environments that constructs a solution by composing it of the pre-calculated shortest solutions of certain sub-problems. This approach prefers short overall solutions. Moreover, we propose a new algorithm for pre-calculating shortest solutions of sub-problems - it is in fact an improvement of the IDA* algorithm. An experimental comparison of our methods with existing techniques is presented in the paper.

In Web-based CSCW (Computer-Supported Cooperative Work) often including cooperative learning, remote members communicate their intentions in cyberspace, using textual sentences, pictures and voice. However, often, communication between members cannot be correctly done and interface errors occur. Different from face-to-face communication, partners' situations including their interest, concentration, boredom, and tiredness cannot be easily transmitted. Oversight and mishearing of remote partners is often overlooked. Besides, it is further difficult to understand their real intentions sufficiently. To overcome these problems, “Augmented Cyberspace” for dependable Web-based CSCW Systems, is proposed, which is also applicable to system such as e-learning, e-commerce, etc. This assesses situations of remote users through timely fusing information of multiple biological sensors and the related contexts. By exploiting the timely assessment, the system augments the cyberspace through emphasizing the situation of remote users or providing warnings in conventional media such as text, image, and voice. Experimental results showed the necessity and feasibility of such assessment by information fusion of multiple sensors.

When research articles introduce new findings or concepts they typically relate them only to knowledge and domain concepts of immediate relevance. However, many domain concepts relevant for the article and its findings are omitted in the text. This may prevent us from retrieving articles of interest when executing a search query. Approaches such as probabilistic latent semantic indexing (PLSI) overcome this limitation by projecting terms in articles to a lower dimensional latent space and best possible matches in this space are identified. Nevertheless, this approach may not perform well enough if the number of explicit knowledge concepts in the articles is too small compared to the amount of knowledge in the domain. The objective of this paper is to address the problem by exploiting a domain knowledge layer: a rich network of associations among knowledge concepts in the domain of interest. We present a new document retrieval framework that i) extracts associations among knowledge concepts from many documents in the literature corpus; ii) and exploits them to improve the retrieval of relevant documents. We test our approach on the problem of retrieval of biomedical documents and show that it outperforms standard Lucene and BM25 information-retrieval methods.

The Multiple ANSwer EXtraction system is a framework for interpreting a conjecture with outermost existentially quantified variables as a question, and extracting multiple answers to the question by repetitive calls to a base system that can report the bindings for the variables in one proof of the conjecture. This paper describes the framework and demonstrates its use on an illustrative example.