Overview: There are a variety of circumstances under which it would be useful to determine that two documents contain similar text, including detecting plagiarism and copyright infringement, and filtering and organizing documents returned by a search engine. The vast amount of digital information

www.ukp.tu-darmstadt.de While the concept of similarity is well grounded in psychology, text similarity is less well-defined. Thus, we analyze text similarity with respect to its definition and the datasets used for evaluation. We formalize text similarity based on the geometric model of conceptual

This paper describes TEXTSIM, a system for determining the similarity between texts. Further, we show the results of a comparison between two various configurations of TEXTSIM; one with and one without any deeper linguistic analysis. To evaluate and compare the two models of TEXTSIM we used two

Measuring the similarity between words, sentences, paragraphs and documents is an important component in various tasks such as information retrieval, document clustering, word-sense disambiguation, automatic essay scoring, short answer grading, machine translation and text summarization

This paper reports experiments on a corpus of news articles from the Financial Times, comparing different text similarity models. First the Ferret system using a method based solely on lexical similarities is used, then methods based on semantic similarities are inves-tigated. Different feature

Abstract. This paper presents a new method for recognizing the text entailment obtained from the text-to-text metric introduced in [3] and from the modified resolution introduced in [12]. In [11], using the directional measure of similarity as presented in [3], which measures the semantic

www.ukp.tu-darmstadt.de We present DKPro Similarity, an open source framework for text similarity. Our goal is to provide a comprehensive repository of text similarity measures which are implemented using standardized interfaces. DKPro Similarity comprises a wide variety of measures ranging from

We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach

Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine