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In this paper we have focused on the problem of automatic prediction of parts of speech in sentences. We present an experimental framework which includes the analysis and the implementation of methods for part of speech (POS) labeling (tagging). We have tested three methods that predict the POS without current word's context and also three context awareness statistic methods. The main goal of our...
Linked Open Data provides a distributed model for the semantic web to create knowledge by publishing public available data and meaningfully interlinking dispersed data sources. It is undeniable that the realization of this goal depends strongly on the quality of the published data. Since, data quality is a multi-dimensional concept which is defined by a number of quality factors, in order to study...
Biometric measurements are now often routinely adopted as a robust means of determining individual identity. Such an approach is clearly beneficial in a variety of scenarios, including those relating to medical environments. In the medical context, however, the use of biometric data can potentially offer other valuable opportunities for harnessing the power of biometrics which have a more direct bearing...
We present here a data mining approach for part-of-speech (POS) tagging, an important Natural language processing (NLP) classification task. We propose a semi-supervised associative classification method for POS tagging. Existing methods for building POS taggers require extensive domain and linguistic knowledge and resources. Our method uses a combination of a small POS tagged corpus and untagged...
Stress affects people's health and well-being of the world's economies. Despite the progress in physiological stress recognition, there are problems that require solutions in the creation of automated systems of stress determination in prolonged real-life situations. These tasks are analysis of stress in daily life, during physical activity and personalization of this analysis. We described these...
In this paper the authors evaluate in context of numerical calculations accuracy classical integer order and direct non-integer based order numerical algorithms of non-integer orders derivatives and integrals computations. Classical integer order based algorithm involves integer and fractional order differentiation and integration operators concatenation to obtain non-integer order. Riemann-Liouville...
Software maintenance tasks such as feature location and traceability link recovery are search-oriented. Most of the recently proposed approaches for automation of search-oriented tasks are based on a traditional text retrieval (TR) model in which documents are unstructured representations of text and queries consist only of keywords. Because source code has structure, approaches based on a structured...
In this paper, we propose a novel method for text/non-text classification in online handwritten document based on Recurrent Neural Network (RNN) and its improved version, Long Short-Term Memory (LSTM) network. The task of classifying strokes in a digital ink document into two classes (text and non-text) can be seen as a sequence labelling task. The bidirectional architecture is used in these networks...
We investigate the task of single-stroke classification into one of three classes (text, figure, or table rule lines). Individual strokes form handwriting structures such as text lines, figures, and tables in combination with peripheral strokes. To classify strokes using local contexts of neighborhood strokes, we propose a composite descriptor that represents in detail the relation between individual...
Extracting key sentences with sentiments from discourses plays an important role in sentiment analysis. Different from general discourses, Internet news has its own fashion of sentiment expression. In this paper, we attempt to extract key sentiment sentences from those Internet news articles. In this paper, we propose a method, called MSF, by using multiple sources features. In our method, for each...
In modern society about 10% of children experience difficulty in learning to read. They suffer from a neuro-developmental disorder called dyslexia. Scientific research has shown that the ability to play action video games improves reading skills of dyslexic children. MADRIGALE research aims at designing and implementing an educational action game oriented to promote, through forms of engaging and...
Sentiment analysis of a movie review plays an important role in understanding the sentiment conveyed by the user towards the movie. In the current work we focus on aspect based sentiment analysis of movie reviews in order to find out the aspect specific driving factors. These factors are the score given to various movie aspects and generally aspects with high driving factors direct the polarity of...
We present a new approach for linear classification optimisation based on Combinatorial Refinement (ComRef) of feature weighting for cognitive signal processing in resource-limited hardware and software like in Cyber-physical systems. Despite simple construction, the approach is able to connect advantages of dimensionality reduction methods and such like combining multiple classifiers resp. Bag-of-classifiers-approaches...
Adaptive program optimizations, such as automatic selection of the expected fastest implementation variant for a computation component depending on runtime context, are important especially for heterogeneous computing systems but require good performance models. Empirical performance models based on trial executions which require no or little human efforts show more practical feasibility if the sampling...
Brain-computer interfaces that directly decode speech could restore communication to locked-in individuals. However, decoding speech from brain signals still faces many challenges. We investigated decoding of phonemes — the smallest separable parts of speech — from ECoG signals during word production. We expanded on previous efforts to identify specific phoneme by identifying phonemes by where in...
Motif detection has raised as an important task in bioinformatics. Recently, the discovery of motifs that are localized relative to a certain biological area has become an important task in many applications. For example, it is used to discover regulatory sequences beside the transcription start site and the neighborhood of known transcription factor binding sites [1]. Therefore, the idea of context...
Context-aware service apps provide a functionality which is personalized for a user's current situation. A main concern of context-aware mobile apps is a substantial consumption of resources. The excessive drain of resources for context acquisition results in slowing down the execution of other apps and shortening the battery life. Hence, we propose Context Acquisition Platform (CAP) to remedy these...
This paper presents a highly parallel solution for cross-document co reference resolution, which can deal with billions of documents that exist in the current web. At the core of our solution lies a novel algorithm for community detection in large scale graphs. We operate on graphs which we construct by representing documents' keywords as nodes and the colocation of those keywords in a document as...
The performances of multicarrier techniques in a spectrum coexistence context are commonly investigated using the power spectral density (PSD) of the coexisting systems' signals. However due to many factors, the PSD approach does not lead to accurate results. Recently, a useful tool called "instantaneous interference tables" has been proposed as an alternative to the PSD-based method leading...
Being transmitted as part of numerous Internet services, geo location data is increasingly bringing hints of people's real-world activities into Internet traffic. This paper focuses on the discovery of key properties that motivate personal activities - locational interests. We propose and design GeoEcho, a mobile traffic analysis system that extracts and analyses a wealth of latitude-longitude geotag...
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