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Search results for: TEXT CLASSIFICATION
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Selection of Relevant Features for Text Classification with K-NN
PublicationIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Methodology for Text Classification using Manually Created Corpora-based Sentiment Dictionary
PublicationThis paper presents the methodology of Textual Content Classification, which is based on a combination of algorithms: preliminary formation of a contextual framework for the texts in particular problem area; manual creation of the Hierarchical Sentiment Dictionary (HSD) on the basis of a topically-oriented Corpus; tonality texts recognition via using HSD for analysing the documents as a collection of topically completed fragments...
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Text Documents Classification with Support Vector Machines
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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A multi-label text message classification method designed for applications in call/contact centre systems
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Two Stage SVM and kNN Text Documents Classifier
PublicationThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations
PublicationThe research presents the methodology of improving the accuracy in sentiment classification in the light of modelling the latent semantic relations (LSR). The objective of this methodology is to find ways of eliminating the limitations of the discriminant and probabilistic methods for LSR revealing and customizing the sentiment classification process (SCP) to the more accurate recognition of text tonality. This objective was achieved...
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The Method of a Two-Level Text-Meaning Similarity Approximation of the Customers’ Opinions
PublicationThe method of two-level text-meaning similarity approximation, consisting in the implementation of the classification of the stages of text opinions of customers and identifying their rank quality level was developed. Proposed and proved the significance of major hypotheses, put as the basis of the developed methodology, notably about the significance of suggestions about the existence of analogies between mathematical bases of...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublicationOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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A survey of automatic speech recognition deep models performance for Polish medical terms
PublicationAmong the numerous applications of speech-to-text technology is the support of documentation created by medical personnel. There are many available speech recognition systems for doctors. Their effectiveness in languages such as Polish should be verified. In connection with our project in this field, we decided to check how well the popular speech recognition systems work, employing models trained for the general Polish language....
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Contextual ontology for tonality assessment
Publicationclassification tasks. The discussion focuses on two important research hypotheses: (1) whether it is possible to construct such an ontology from a corpus of textual document, and (2) whether it is possible and beneficial to use inferencing from this ontology to support the process of sentiment classification. To support the first hypothesis we present a method of extraction of hierarchy of contexts from a set of textual documents...
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How Specific Can We Be with k-NN Classifier?
PublicationThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Text classifiers for automatic articles categorization
PublicationThe article concerns the problem of automatic classification of textual content. We present selected methods for generation of documents representation and we evaluate them in classification tasks. The experiments have been performed on Wikipedia articles classified automatically to their categories made by Wikipedia editors.
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An extension to the FEEDB Multimodal Database of Facial Expressions and Emotions
PublicationFEEDB is a multimodal database that contains recordings of people expressing different emotions, captured by using a Microsoft Kinect sensor. Data were originally provided in the device’s proprietary format (XED), requiring both the Microsoft Kinect Studio application and a Kinect sensor attached to the system to use the files. In this paper, we present an extension of the database. For a selection of recordings, we also provide...
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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublicationVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Selecting Features with SVM
PublicationA common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...
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A system for Direction-Of-Arrival estimation in ISM 2.4 GHz frequency band based on ESPAR antenna and SDR technology
PublicationDetermination of the direction of the signal arrival (DOA) finds many applications in various areas of science and industry. Knowledge of DOA is used, among others to determine the position of a satellite with a low Earth orbit (LEO), localization of people and things as well as in research of wireless communication systems, for instance the determination of the number of...
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Towards Healthcare Cloud Computing
PublicationIn this paper we present construction of a software platform for supporting medical research teams, in the area of impedance cardiography, called IPMed. Using the platform, research tasks will be performed by the teams through computer-supported cooperative work. The platform enables secure medical data storing, access to the data for research group members, cooperative analysis of medical data and provide analysis supporting tools...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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External Validation Measures for Nested Clustering of Text Documents
PublicationAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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High Performance Control of AC Drives with Matlab/ Simulink
PublicationExplore this indispensable update to a popular graduate text on electric drive techniques and the latest converters used in industry. The Second Edition of High Performance Control of AC Drives with Matlab®/Simulink delivers an updated and thorough overview of topics central to the understanding of AC motor drive systems. The book includes new material on medium voltage drives, covering state-of-the-art technologies and challenges...
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Industrial Heritage in sacrifice zones, The potential of Bocamina I & II Thermoelectric in Coronel, Chile
PublicationThis work aims to present the recovery potential of the Chilean Sacrifice Zones, urban areas affected by high amounts of pollution caused by industrial activities. It centers in the case of “Bocamina I & II”, two Thermoelectric based in the city of Coronel, southern Chile. A settlement historically related to the mining processes. These plants operated for decades supplying the national energy...