Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with large increase volume of textual data that is produced daily. Traditional approaches for calculating degree two texts, based on words they share, do not perform well because similar may be written differen...

In natural language processing, short-text semantic similarity (STSS) is a very prominent field. It has significant impact on broad range of applications, such as question–answering systems, information retrieval, entity recognition, text analytics, sentiment classification, and so on. Despite their widespread use, many traditional machine learning techniques are incapable identifying the seman...

Because of the massive amount textual information accessible today, automated extraction text summarization is one most extensively used ways to organize information. The mechanisms help extract important topics data from a given set documents. Extractive method for providing representative summary by choosing pertinent sentences original text. multi-document systems' primary goal decrease quan...

Conventional approaches to text analysis and information retrieval which measured document similarity by using considering all of the information in texts are a relatively inefficiency for processing large text collections in heterogeneous subject areas. This paper outlined a new text manipulation system FA-Sim that is useful for retrieving information in large heterogeneous texts and for recog...

A study of lhe relations between the perceptive similarity of voices and physical measures of the speech signal has been carried out. The goal of this study was to identify a set of acoustic parameters which contribute mosl to the voice discrimination process. We worked on a corpus of Iogatoms CVCV. Ten male speakers uttering nine items were considered and a single sample of each item was used....

We propose the Normalized Relevance Distance (NRD): a robust metric for computing semantic relatedness between terms. NRD makes use of a controlled reference corpus for a statistical analysis. The analysis is based on the relevance scores and joint occurrence of terms in documents. On the basis of established reference datasets, we demonstrate that NRD does not require sophisticated data tuning...

Content-based music comparison is a task where no musical similarity measure can perform well in all possible cases. In this paper we will show that a careful combination of different similarity measures in an ensemble measure, will behave more robust than any of the included individual measures when applied as stand-alone measures. For the experiments we have used five state-of-the-art polypho...