This research focuses on real-time gesture learning and recognition. Events arrive in a continuous stream without explicitly given boundaries. To obtain temporal accuracy, we need to consider the lag between the detection of an event and any effects we wish to trigger with it. Two methods for real time gesture recognition using a Nintendo Wii controller are presented. The first detects gestures...

Web corpora are often constructed automatically, and their contents are therefore often not well understood. One technique for assessing the composition of such a web corpus is to empirically measure its similarity to a reference corpus whose composition is known. In this paper we evaluate a number of measures of corpus similarity, including a method based on topic modelling which has not been ...

The notion of similarity is an important one in data mining. It can be used to provide useful structural information on data as well as enable clustering. In this paper we present an elegant method for measuring the similarity between homogeneous datasets. The algorithm presented is eÆcient in storage and scale, has the ability to adjust to time constraints. and can provide the user with likely...

This paper introduces CL-ESA, a new multilingual retrieval model for the analysis of cross-language similarity. The retrieval model exploits the multilingual alignment of Wikipedia: given a document d written in language L we construct a concept vector d for d, where each dimension i in d quantifies the similarity of d with respect to a document di chosen from the “L-subset” of Wikipedia. Likew...

In this study, feature selection in classi cation based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classi er. ...

Measuring the similarity between two texts is a fundamental problem in many NLP and IR applications. Among the existing approaches, the cosine measure of the term vectors representing the original texts has been widely used, where the score of each term is often determined by a TFIDF formula. Despite its simplicity, the quality of such cosine similarity measure is usually domain dependent and d...

This paper describes the system used by the LIPN team in the Semantic Textual Similarity task at SemEval 2013. It uses a support vector regression model, combining different text similarity measures that constitute the features. These measures include simple distances like Levenshtein edit distance, cosine, Named Entities overlap and more complex distances like Explicit Semantic Analysis, WordN...

scott and szewczyk in technometrics, 2001, have introduced a similarity measure for twodensities f1 and f2 , by1, 21 21 1 2 2( , ), ,f fsim f ff f f f< >=< >< >wheref1, f2 f1(x, θ1)f2(x, θ2)dx.+∞−∞< >=∫sim(f1, f2) has some appropriate properties that can be suitable measures for the similarity of f1 and f2 .however, due to some restrictions on the value of parameters and the kind of densities, ...

In this paper, the concept of an augmented session is used to derive different augmented session similarity measures. It is believed that augmented session similarity measures are more realistic and represent session similarities based on the web user’s habits, interest, and expectations as compared to simple binary cosine measure. We apply a relational fuzzy c-mean clustering approach to evalu...

News items play an increasingly important role in the current business decision processes. Due to the large amount of news published every day it is difficult to find the new items of one’s interest. One solution to this problem is based on employing recommender systems. Traditionally, these recommenders use term extraction methods like TF-IDF combined with the cosine similarity measure. In thi...