This article reports on a modification of the user-kNN algorithm that measures the similarity between users based on the similarity of text reviews, instead of ratings. We investigate the performance of text semantic similarity measures and we evaluate our text-based user-kNN approach by comparing it to a range of ratings-based approaches in a ratings prediction task. We do so by using datasets...

The concept of semantic similarity is an important element in many applications such as information extraction, information retrieval, document clustering and ontology learning. Most of the previous works regarding semantic similarity measures have been traditionally defined between words or concepts (i.e. word-to-word similarity), thus ignoring the text or sentence that the concepts participat...

We present a fuzzy similarity approach to solve a text categorization problem. The effectiveness of various fuzzy conjunction and disjunction operators used in fuzzy similarity formula and several document representations were evaluated using test sets from three text document collections. Based on empirical results obtained from using these collections, a special case of the fuzzy similarity f...

Text similarity detection aims at measuring the degree of similarity between a pair of texts. Corpora available for text similarity detection are designed to evaluate the algorithms to assess the paraphrase level among documents. In this paper we present a textual German corpus for similarity detection. The purpose of this corpus is to automatically assess the similarity between a pair of texts...

We present a new composite similarity metric that combines information from multiple linguistic indicators to measure semantic distance between pairs of small textual units. Several potential features are investigated and an optireal combination is selected via machine learning. We discuss a more restrictive definition of similarity than traditional, document-level and information retrieval-ori...

Measuring the similarity between documents and queries has been extensively studied in information retrieval. However, there are a growing number of tasks that require computing the similarity between two very short segments of text. These tasks include query reformulation, sponsored search, and image retrieval. Standard text similarity measures perform poorly on such tasks because of data spar...

Short text similarity measure is the basis of classification and duplicate checking of the short texts. Allowing for the insufficient consideration of the sentence semantic and structure information in similarity calculation between two short texts, we propose a novel method of short text similarity calculation based on double vector space model on the basis of traditional vector space model. C...

We explore automated discovery of topicallycoherent segments in speech or text sequences. We give two new discriminative topic segmentation algorithms which employ a new measure of text similarity based on word co-occurrence. Both algorithms function by finding extrema in the similarity signal over the text, with the latter algorithm using a compact support-vector based description of a window ...

Sentence similarity plays an important role in text-related research and applications. It is closely related to word similarity and document similarity. The statistical similarity measures between sentences, based on symbolic characteristics and structural information, could measure the similarity between sentences without any prior knowledge but only on the statistical information of sentences...