Search results for: Text Miner
572 Data Mining Using Learning Automata
Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri
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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1923571 STATISTICA Software: A State of the Art Review
Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha
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Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.
Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2598570 Off-Line Hand Written Thai Character Recognition using Ant-Miner Algorithm
Authors: P. Phokharatkul, K. Sankhuangaw, S. Somkuarnpanit, S. Phaiboon, C. Kimpan
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Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).Keywords: Hand written, Thai character recognition, Ant-mineralgorithm, distinct feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1919569 A Design for Customer Preferences Model by Cluster Analysis of Geometric Features and Customer Preferences
Authors: Yuan-Jye Tseng, Ching-Yen Chen
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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.
Keywords: Cluster analysis, customer preferences, design evaluation, design for customer preferences, product design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 756568 W3-Miner: Mining Weighted Frequent Subtree Patterns in a Collection of Trees
Authors: R. AliMohammadzadeh, M. Haghir Chehreghani, A. Zarnani, M. Rahgozar
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Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover.Keywords: Semi-Structured Data Mining, Anti-Monotone Property, Trees.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1367567 Continuous Text Translation Using Text Modeling in the Thetos System
Authors: Nina Suszczanska, Przemyslaw Szmal, Slawomir Kulikow
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In the paper a method of modeling text for Polish is discussed. The method is aimed at transforming continuous input text into a text consisting of sentences in so called canonical form, whose characteristic is, among others, a complete structure as well as no anaphora or ellipses. The transformation is lossless as to the content of text being transformed. The modeling method has been worked out for the needs of the Thetos system, which translates Polish written texts into the Polish sign language. We believe that the method can be also used in various applications that deal with the natural language, e.g. in a text summary generator for Polish.Keywords: anaphora, machine translation, NLP, sign language, text syntax.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1643566 OCR/ICR Text Recognition Using ABBYY FineReader as an Example Text
Authors: A. R. Bagirzade, A. Sh. Najafova, S. M. Yessirkepova, E. S. Albert
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This article describes a text recognition method based on Optical Character Recognition (OCR). The features of the OCR method were examined using the ABBYY FineReader program. It describes automatic text recognition in images. OCR is necessary because optical input devices can only transmit raster graphics as a result. Text recognition describes the task of recognizing letters shown as such, to identify and assign them an assigned numerical value in accordance with the usual text encoding (ASCII, Unicode). The peculiarity of this study conducted by the authors using the example of the ABBYY FineReader, was confirmed and shown in practice, the improvement of digital text recognition platforms developed by Electronic Publication.
Keywords: ABBYY FineReader system, algorithm symbol recognition, OCR/ICR techniques, recognition technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 754565 On-Road Text Detection Platform for Driver Assistance Systems
Authors: Guezouli Larbi, Belkacem Soundes
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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered as a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.
Keywords: Text detection, CNN, PZM, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 140564 Powerful Tool to Expand Business Intelligence: Text Mining
Authors: Li Gao, Elizabeth Chang, Song Han
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With the extensive inclusion of document, especially text, in the business systems, data mining does not cover the full scope of Business Intelligence. Data mining cannot deliver its impact on extracting useful details from the large collection of unstructured and semi-structured written materials based on natural languages. The most pressing issue is to draw the potential business intelligence from text. In order to gain competitive advantages for the business, it is necessary to develop the new powerful tool, text mining, to expand the scope of business intelligence. In this paper, we will work out the strong points of text mining in extracting business intelligence from huge amount of textual information sources within business systems. We will apply text mining to each stage of Business Intelligence systems to prove that text mining is the powerful tool to expand the scope of BI. After reviewing basic definitions and some related technologies, we will discuss the relationship and the benefits of these to text mining. Some examples and applications of text mining will also be given. The motivation behind is to develop new approach to effective and efficient textual information analysis. Thus we can expand the scope of Business Intelligence using the powerful tool, text mining.Keywords: Business intelligence, document warehouse, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2646563 Optimal Classifying and Extracting Fuzzy Relationship from Query Using Text Mining Techniques
Authors: Faisal Alshuwaier, Ali Areshey
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Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a concept graph generation mechanism, which is based on a text classification and optimal fuzzy relationship extraction. Furthermore, the work presented in this paper explains the application of fuzzy relationship extraction and branch and bound (BB) method to simplify the texts.
Keywords: Extraction, Max-Prod, Fuzzy Relations, Text Mining, Memberships, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2171562 A Web Text Mining Flexible Architecture
Authors: M. Castellano, G. Mastronardi, A. Aprile, G. Tarricone
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Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from notstructured o semi-structured data. This aspect is fundamental because much of the Web information is semi-structured due to the nested structure of HTML code, much of the Web information is linked, much of the Web information is redundant. Web Text Mining helps whole knowledge mining process to mining, extraction and integration of useful data, information and knowledge from Web page contents. In this paper, we present a Web Text Mining process able to discover knowledge in a distributed and heterogeneous multiorganization environment. The Web Text Mining process is based on flexible architecture and is implemented by four steps able to examine web content and to extract useful hidden information through mining techniques. Our Web Text Mining prototype starts from the recovery of Web job offers in which, through a Text Mining process, useful information for fast classification of the same are drawn out, these information are, essentially, job offer place and skills.Keywords: Web text mining, flexible architecture, knowledgediscovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2650561 Key Based Text Watermarking of E-Text Documents in an Object Based Environment Using Z-Axis for Watermark Embedding
Authors: Mussarat Abdullah, Fazal Wahab
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Data hiding into text documents itself involves pretty complexities due to the nature of text documents. A robust text watermarking scheme targeting an object based environment is presented in this research. The heart of the proposed solution describes the concept of watermarking an object based text document where each and every text string is entertained as a separate object having its own set of properties. Taking advantage of the z-ordering of objects watermark is applied with the z-axis letting zero fidelity disturbances to the text. Watermark sequence of bits generated against user key is hashed with selected properties of given document, to determine the bit sequence to embed. Bits are embedded along z-axis and the document has no fidelity issues when printed, scanned or photocopied.Keywords: Digital Watermarking, Object Based Environment, Watermark, z-ordering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1677560 Application of Smooth Ergodic Hidden Markov Model in Text to Speech Systems
Authors: Armin Ghayoori, Faramarz Hendessi, Asrar Sheikh
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In developing a text-to-speech system, it is well known that the accuracy of information extracted from a text is crucial to produce high quality synthesized speech. In this paper, a new scheme for converting text into its equivalent phonetic spelling is introduced and developed. This method is applicable to many applications in text to speech converting systems and has many advantages over other methods. The proposed method can also complement the other methods with a purpose of improving their performance. The proposed method is a probabilistic model and is based on Smooth Ergodic Hidden Markov Model. This model can be considered as an extension to HMM. The proposed method is applied to Persian language and its accuracy in converting text to speech phonetics is evaluated using simulations.Keywords: Hidden Markov Models, text, synthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1538559 RB-Matcher: String Matching Technique
Authors: Rajender Singh Chillar, Barjesh Kochar
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All Text processing systems allow their users to search a pattern of string from a given text. String matching is fundamental to database and text processing applications. Every text editor must contain a mechanism to search the current document for arbitrary strings. Spelling checkers scan an input text for words in the dictionary and reject any strings that do not match. We store our information in data bases so that later on we can retrieve the same and this retrieval can be done by using various string matching algorithms. This paper is describing a new string matching algorithm for various applications. A new algorithm has been designed with the help of Rabin Karp Matcher, to improve string matching process.Keywords: Algorithm, Complexity, Matching-patterns, Pattern, Rabin-Karp, String, text-processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1755558 An Semantic Algorithm for Text Categoritation
Authors: Xu Zhao
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Text categorization techniques are widely used to many Information Retrieval (IR) applications. In this paper, we proposed a simple but efficient method that can automatically find the relationship between any pair of terms and documents, also an indexing matrix is established for text categorization. We call this method Indexing Matrix Categorization Machine (IMCM). Several experiments are conducted to show the efficiency and robust of our algorithm.
Keywords: Text categorization, Sub-space learning, Latent Semantic Space
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1453557 Binarization of Text Region based on Fuzzy Clustering and Histogram Distribution in Signboards
Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee
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In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.Keywords: Text detection, edge profile, signboard image, fuzzy clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2216556 An Edge-based Text Region Extraction Algorithm for Indoor Mobile Robot Navigation
Authors: Jagath Samarabandu, Xiaoqing Liu
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Using bottom-up image processing algorithms to predict human eye fixations and extract the relevant embedded information in images has been widely applied in the design of active machine vision systems. Scene text is an important feature to be extracted, especially in vision-based mobile robot navigation as many potential landmarks such as nameplates and information signs contain text. This paper proposes an edge-based text region extraction algorithm, which is robust with respect to font sizes, styles, color/intensity, orientations, and effects of illumination, reflections, shadows, perspective distortion, and the complexity of image backgrounds. Performance of the proposed algorithm is compared against a number of widely used text localization algorithms and the results show that this method can quickly and effectively localize and extract text regions from real scenes and can be used in mobile robot navigation under an indoor environment to detect text based landmarks.
Keywords: Landmarks, mobile robot navigation, scene text, text localization and extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2911555 Text Retrieval Relevance Feedback Techniques for Bag of Words Model in CBIR
Authors: Nhu Van NGUYEN, Jean-Marc OGIER, Salvatore TABBONE, Alain BOUCHER
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The state-of-the-art Bag of Words model in Content- Based Image Retrieval has been used for years but the relevance feedback strategies for this model are not fully investigated. Inspired from text retrieval, the Bag of Words model has the ability to use the wealth of knowledge and practices available in text retrieval. We study and experiment the relevance feedback model in text retrieval for adapting it to image retrieval. The experiments show that the techniques from text retrieval give good results for image retrieval and that further improvements is possible.Keywords: Relevance feedback, bag of words model, probabilistic model, vector space model, image retrieval
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2099554 A System to Adapt Techniques of Text Summarizing to Polish
Authors: Marcin Ciura, Damian Grund, S
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This paper describes a system, in which various methods of text summarizing can be adapted to Polish. A structure of the system is presented. A modular construction of the system and access to the system via the Internet are signaled.
Keywords: Automatic summary generation, linguistic analysis, text generation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1535553 A Proposed Hybrid Approach for Feature Selection in Text Document Categorization
Authors: M. F. Zaiyadi, B. Baharudin
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Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.Keywords: Ant colony optimization, feature selection, information gain, text categorization, text representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2054552 Graph-Based Text Similarity Measurement by Exploiting Wikipedia as Background Knowledge
Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang
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Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.Keywords: Text classification, Text clustering, Text similarity, Wikipedia
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2104551 Effects of Gamma Radiation on Tomato Leafminer, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae)
Authors: Akın Kuyulu, Hanife Genç
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In present study, it was aimed to evaluate the gamma radiation impacts on tomato leaf miner at different biological stages. The laboratory colony of tomato leaf miner was used to set up the experiments. Different biological stages of the insects (eggs, 4th instars and pupae) were irradiated using Cobalt-60 at doses of 0 (control), 100 Gray (Gy), 200 Gy, 300 Gy and 400 Gy in Cos-44HH-N source, at dose rate of 480 Gy/h. After irradiation, the eggs were incubated until hatching; the mature larvae were reared to complete their developments. Adult emergences from irradiated pupae were also evaluated. The results showed that there were no egg hatching at all tested irradiation doses. Although, the pupal percentages of irradiated mature larvae were 54%, 15% and 8% at doses of 100 Gy, 200 Gy and 300 Gy respectively, there were no adult emergences from irradiated mature larvae. On the other hand, the adult emergences were observed from irradiated pupae, decreased as radiation doses increased along with malformed adult appearance. Male and female individuals were out crossed with laboratory reared adults. Fecundity was correlated with radiation doses.Keywords: Irradiation, tomato, tomato leafminer, Tuta absoluta.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1577550 Dynamic Decompression for Text Files
Authors: Ananth Kamath, Ankit Kant, Aravind Srivatsa, Harisha J.A
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Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.Keywords: Compression, Dynamic Decompression, Text file format, Portable Document Format, Compression Ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1750549 Journals Subheadlines Text Extraction Using Wavelet Thresholding and New Projection Profile
Authors: Davod Zaravi, Habib Rostami, Alireza Malahzaheh, S. S. Mortazavi
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In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.
Keywords: Text extraction, colored cover sheet, wavelet threshold, region of interest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1636548 Text-Mining Approach for Evaluation of Affective Management Practices
Authors: Masaaki Saito, Qin Tang, Hiroyuki Umemuro
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The purpose of this paper is to propose a text mining approach to evaluate companies- practices on affective management. Affective management argues that it is critical to take stakeholders- affects into consideration during decision-making process, along with the traditional numerical and rational indices. CSR reports published by companies were collected as source information. Indices were proposed based on the frequency and collocation of words relevant to affective management concept using text mining approach to analyze the text information of CSR reports. In addition, the relationships between the results obtained using proposed indices and traditional indicators of business performance were investigated using correlation analysis. Those correlations were also compared between manufacturing and non-manufacturing companies. The results of this study revealed the possibility to evaluate affective management practices of companies based on publicly available text documents.Keywords: Affective management, Affect, Stakeholder, Text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1834547 Meta-Classification using SVM Classifiers for Text Documents
Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp
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Text categorization is the problem of classifying text documents into a set of predefined classes. In this paper, we investigated three approaches to build a meta-classifier in order to increase the classification accuracy. The basic idea is to learn a metaclassifier to optimally select the best component classifier for each data point. The experimental results show that combining classifiers can significantly improve the accuracy of classification and that our meta-classification strategy gives better results than each individual classifier. For 7083 Reuters text documents we obtained a classification accuracies up to 92.04%.Keywords: Meta-classification, Learning with Kernels, Support Vector Machine, and Performance Evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1600546 Clustering Unstructured Text Documents Using Fading Function
Authors: Pallav Roxy, Durga Toshniwal
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Clustering unstructured text documents is an important issue in data mining community and has a number of applications such as document archive filtering, document organization and topic detection and subject tracing. In the real world, some of the already clustered documents may not be of importance while new documents of more significance may evolve. Most of the work done so far in clustering unstructured text documents overlooks this aspect of clustering. This paper, addresses this issue by using the Fading Function. The unstructured text documents are clustered. And for each cluster a statistics structure called Cluster Profile (CP) is implemented. The cluster profile incorporates the Fading Function. This Fading Function keeps an account of the time-dependent importance of the cluster. The work proposes a novel algorithm Clustering n-ary Merge Algorithm (CnMA) for unstructured text documents, that uses Cluster Profile and Fading Function. Experimental results illustrating the effectiveness of the proposed technique are also included.Keywords: Clustering, Text Mining, Unstructured TextDocuments, Fading Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1976545 A Content Vector Model for Text Classification
Authors: Eric Jiang
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As a popular rank-reduced vector space approach, Latent Semantic Indexing (LSI) has been used in information retrieval and other applications. In this paper, an LSI-based content vector model for text classification is presented, which constructs multiple augmented category LSI spaces and classifies text by their content. The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms. The proposed classifier has been applied to email classification and its experiments on a benchmark spam testing corpus (PU1) have shown that the approach represents a competitive alternative to other email classifiers based on the well-known SVM and naïve Bayes algorithms.Keywords: Feature Selection, Latent Semantic Indexing, Text Classification, Vector Space Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1876544 Narrative and Expository Text Reading Comprehension by Fourth Grade Spanish-Speaking Children
Authors: Mariela V. De Mier, Veronica S. Sanchez Abchi, Ana M. Borzone
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This work aims to explore the factors that have an incidence in reading comprehension process, with different type of texts. In a recent study with 2nd, 3rd and 4th grade children, it was observed that reading comprehension of narrative texts was better than comprehension of expository texts. Nevertheless it seems that not only the type of text but also other textual factors would account for comprehension depending on the cognitive processing demands posed by the text. In order to explore this assumption, three narrative and three expository texts were elaborated with different degree of complexity. A group of 40 fourth grade Spanish-speaking children took part in the study. Children were asked to read the texts and answer orally three literal and three inferential questions for each text. The quantitative and qualitative analysis of children responses showed that children had difficulties in both, narrative and expository texts. The problem was to answer those questions that involved establishing complex relationships among information units that were present in the text or that should be activated from children’s previous knowledge to make an inference. Considering the data analysis, it could be concluded that there is some interaction between the type of text and the cognitive processing load of a specific text.
Keywords: comprehension, textual factors, type of text, processing demands.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1394543 A Talking Head System for Korean Text
Authors: Sang-Wan Kim, Hoon Lee, Kyung-Ho Choi, Soon-Young Park
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A talking head system (THS) is presented to animate the face of a speaking 3D avatar in such a way that it realistically pronounces the given Korean text. The proposed system consists of SAPI compliant text-to-speech (TTS) engine and MPEG-4 compliant face animation generator. The input to the THS is a unicode text that is to be spoken with synchronized lip shape. The TTS engine generates a phoneme sequence with their duration and audio data. The TTS applies the coarticulation rules to the phoneme sequence and sends a mouth animation sequence to the face modeler. The proposed THS can make more natural lip sync and facial expression by using the face animation generator than those using the conventional visemes only. The experimental results show that our system has great potential for the implementation of talking head for Korean text.Keywords: Talking head, Lip sync, TTS, MPEG4.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1482