Optimal feature subset selection is an important pre-processing step for classification in many real life problems where number of dimensions of feature space is large and some features are may be irrelevant or redundant. One example of such a situation is genes expression profile data to classify among normal and cancerous samples. Contribution of this paper is five folds. Similarity-dissimila...

Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...

In this paper, we describe our QU-BIGIR system for the Arabic subtask D of the SemEval 2017 Task 3. Our approach builds on our participation in the past version of the same subtask. This year, our system uses different similarity features that encodes lexical and semantic pairwise similarity of text pairs. In addition to wellknown similarity measures such as cosine similarity, we use other meas...

This paper describes a method of mapping music into a semantic space that can be used for similarity measurement, classification, and music information retrieval. The value along each dimension of this anchor space is computed as the output from a pattern classifier which is trained to measure a particular semantic feature. In anchor space, distributions that represent objects such as artists o...

This paper describes the system developed by our team (HLTC-HKUST) for task 1 of SemEval 2015 workshop about paraphrase classification and semantic similarity in Twitter. We trained a neural network classifier over a range of features that includes translation metrics, lexical and syntactic similarity score and semantic features based on semantic roles. The neural network was trained taking int...

Non-Factoid Question Answering (QA) is the next generation of textual QA systems, which gives passage level summaries for a natural language query, posted by user. The main issue lies in appropriateness generated summary. This paper proposes framework non-factoid system, has three components: (i) A deep neural network classifier, produces sentence vector considering word correlation and context...

In this paper we present a binary graph classifier (BGC) which allows to classify large, unweighted, undirected graphs. The main idea of this classifier is to decompose a graph locally in generalized trees forming the tree set of a graph and to compare the tree sets of graphs by a generalized tree-similarity algorithm (GTSA). We apply our BGC to networks representing co-expressed genes from DNA...

Similarity search and data mining on time series databases has recently attracted much attention. In this paper, we represent a data object by several time series-valued attributes. Although this kind of object representation is very natural and straightforward in many applications, there has not been much research on data mining methods for objects of this special type. In this paper, we propo...

K-nearest neighbor (k-NN) classification is a powerful and simple method for classification. k-NN classifiers approximate a Bayesian classifier for a large number of data samples. The accuracy of k-NN classifier relies on the distance metric used for calculating nearest neighbor and features used for instances in training and testing data. In this paper we use deep neural networks (DNNs) as a f...

This paper presents a revised version of an unsupervised and knowledge-free morpheme boundary detection algorithm based on letter successor variety (LSV) and a trie classifier (Bordag, 2006a). Additionally a morphemic analysis based on contextual similarity provides knowledge about relatedness of the found morphs. For the boundary detection the challenge of increasing recall of found morphs whi...