Abstract: In present front-line of Big Data, prediction tasks over the nodes and edges in complex deep architecture needs a careful representation of features by assigning hundreds of thousands, or even millions of labels and samples for infor

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Abstract: This paper presents an overview of different graph-based representations proposed to solve text classification tasks. The core of this manuscript is to highlight the importance of enriched/non-enriched co-occurrence graphs as an alternativ

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Abstract: In this paper, I deal with property modifiers defined as functions that associate a given root property P with a modified property [ M P ]. Property modifiers typically divide into four kinds, namely intersective, subsective , privativ

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Abstract: Computer Assisted Language Learnin g (CALL) systems is used as a media to teach a language without the need for a class room or a teacher. CALL systems include language lessons and exercises to enhance the learners’ vocabulary, gram

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Abstract: Sentence similarity computing is increasingly growing in several applications, such as question answering, machine-translation, information retrieval and automatic abstracting systems. This paper firstly sums up several methods to cal

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Abstract: Lexicalization of the input of sequential taggers has gone a long way since it was invented by Molina and Pla [4]. In this paper we thoroughly investigate the method introduced by Indig and Endrédy [2] to find out the best lexicalization level for chunking an

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Abstract: Studying Arabic nominal sentences is important to analyze and annotate successfully Arabic corpora. This type of sentences is frequent in Arabic text and speech. Transducers can be used to realize local grammars and treat several lin

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Abstract: The subjectivity detection is an important binary classification task that aims at distinguishing natural language texts as opinionated (positive or negative) and non-opinionated (neutral). In this paper, we develop and apply

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Abstract: Social media is a rich source of information and opinion, with exponential data growth rate. However social media posts are difficult to analyze since they are brief, unstructured and noisy. Interestingly, many social media posts are about

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Abstract: Focusing on the current multilingual scenario in social media, this paper reports automatic extraction of named entities (NE) from code-mixed cross-script social media data. Our prime target is to extract NE for question answering. This paper also introduces

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Abstract: An evaluation metric is an absolute necessity for measuring the performance of any system and complexity of any data. In this paper, we have discussed how to determine the level of complexity of code-mixed social media texts t

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Abstract: In this study, we identify the features of an article that encourage people to leave a comment for it. The volume of the received comments for a news article shows its importance. It also indirectly indicates the amount of influence a n

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Abstract: Several proposed metrics of MT Evaluation like BLEU have been criti cized for their poor performance in evaluating machine translations. Languages like Hindi which have relatively free word - order and are morphologically rich

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Abstract: Corpus may be considered as fuel for the data driven approaches of machine translation. Parallel corpus building is a labour intensive task, which makes it a costly and scarce resource. Full potential of available data needs to be exploited and

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Abstract: Balinese ancient palm leaf manuscripts record many important kn owledges about world civilization histories. They vary from ordinary texts to Bali’s most sacred writings. In reality, the majority of Balinese can not read it because of lan

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Abstract: The objective of the present work is to automatically extract the cause and effect from discourse analyzed biomedical corpus. Cause - effect is defined as a relation established between two events, where first event acts as

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Abstract: To improve the classification performance for Chinese short text with automatic semantic feature selection, in this paper we propose the Hybrid Attention Networks (HANs) which combines the word- and character-level selective attention

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Abstract: High dimensionality of the feature space is one of the difficulty that affect short message service (SMS) classification performance. Some studies used feature selection methods to pick up some features, while other studies used the

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Abstract: This paper introduces a novel neural network model for question answering, the entity-based memory network . It enhances neural networks’ ability of representing and calculating information over a long period by keeping records

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Abstract: The main goal of reporting in the financial system is to ensure high quality and useful information about the financial position of firms, and to make it available to a wide range of users, including existing and potential investors, financial

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Abstract: Speech segregation is one of the most difficult tasks in speech processing. This paper uses computational auditory scene analysis, support vector machine classifier, and post - processing on binary mask to separate speech from

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Abstract: We present a minimum description length- based algorithm for finding the regular correspondences between related languages and show how it can be used to quantify the similarity between not only pairs, but whole groups of lang

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Abstract: It is known that, depending on the numerical method, the simulation accuracy of a spiking neuron increases monotonically and that the computational cost increases in a power-law complexity as the time step reduces. Moreover, the mechanism re

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Abstract: The design and the proof of correctness of distributed algorithms in dynamic networks are difficult tasks. These networks are characterized by frequent topology changes due to unpredictable appearance and disappearance of mobil

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Abstract: The typical semiclassical wave version of the unsorted database search algorithm based on a system of coupled simple harmonic oscillators does not consider an important ingredient of Grover’s original algorithm as it is quantum entanglement. The role of enta

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