Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416588
S. Garg, Amioy Kumar, M. Hanmandlu
This paper presents a new biometric system based on the outer surface of the finger nail. There has not been any attempt in utilizing nail shape and texture for human authentication. The nail bed information, imitated on the nail surface proves to be a very unique and stable biometric identifier for personal authentication. However, research literature presents some complex set-up and the use of interferometer technique for extraction of nail bed details. In this work we propose a very simple and convenient method to segment nail surface from the user hand and use it as a biometric identifier. We further extract texture feature from nail-surface and our experimental results from 180 users validate the contributions from this paper.
{"title":"Biometric authentication using finger nail surface","authors":"S. Garg, Amioy Kumar, M. Hanmandlu","doi":"10.1109/ISDA.2012.6416588","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416588","url":null,"abstract":"This paper presents a new biometric system based on the outer surface of the finger nail. There has not been any attempt in utilizing nail shape and texture for human authentication. The nail bed information, imitated on the nail surface proves to be a very unique and stable biometric identifier for personal authentication. However, research literature presents some complex set-up and the use of interferometer technique for extraction of nail bed details. In this work we propose a very simple and convenient method to segment nail surface from the user hand and use it as a biometric identifier. We further extract texture feature from nail-surface and our experimental results from 180 users validate the contributions from this paper.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121611375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416567
Pranshu Saxena, S. Singh
In this research paper we are introducing a classification approach for determining the texture feature and the subsequent classification of histopathological digital image i.e. applied computer-aided grading of follicular lymphoma (FL) and Neuroblastoma (NB) from whole-slide tissue samples. Basic idea behind this research is to distinguish among nuclei, cytoplasm, extracellular material and red blood cells from H&E stained input image so that doctors (radiologist) can provide better judgment during the prognosis of histopathological image that sometimes wrongly concluded. In this study we proposed a noble algorithm in which we convolve our H&E stained pathological images with 12 different orientation masks, resulting in an output of 12 different representations (corresponding to 12 different orientations) of our H&E stained input image. The information included in the 12 representations coming from the application of Gaussian filter is summarized in twelve images that correspond to each of the orientations used in the filters. We then combine these 12 images into one textured image represented as a 3-dimensional representation of input image. Experimental results on FL & NB demonstrate that the proposed approach outperforms the gray level based texture analysis.
{"title":"Noble approach for texture classification of H&E stained histopathological image by Gaussian wavelet","authors":"Pranshu Saxena, S. Singh","doi":"10.1109/ISDA.2012.6416567","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416567","url":null,"abstract":"In this research paper we are introducing a classification approach for determining the texture feature and the subsequent classification of histopathological digital image i.e. applied computer-aided grading of follicular lymphoma (FL) and Neuroblastoma (NB) from whole-slide tissue samples. Basic idea behind this research is to distinguish among nuclei, cytoplasm, extracellular material and red blood cells from H&E stained input image so that doctors (radiologist) can provide better judgment during the prognosis of histopathological image that sometimes wrongly concluded. In this study we proposed a noble algorithm in which we convolve our H&E stained pathological images with 12 different orientation masks, resulting in an output of 12 different representations (corresponding to 12 different orientations) of our H&E stained input image. The information included in the 12 representations coming from the application of Gaussian filter is summarized in twelve images that correspond to each of the orientations used in the filters. We then combine these 12 images into one textured image represented as a 3-dimensional representation of input image. Experimental results on FL & NB demonstrate that the proposed approach outperforms the gray level based texture analysis.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121907757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416658
Mau Uyen Nguyen, L. Ngo, Dao Thanh Tinh
Obstacle detection is a fundamental issue of robot navigation and there have been several proposed methods for this problem. In this paper, we propose a new approach to find out obstacles on Depth Camera streams. The proposed approach consists of three stages. First, preprocessing stage is for noise removal. Second, different depths in a frame are clustered based on the Interval Type-2 Fuzzy Subtractive Clustering algorithm. Third, the objects of interest are detected from the obtained clusters. Beside that, it gives an improvement in the Interval Type-2 Fuzzy Subtractive Clustering algorithm to reduce the time consuming. In theory, it is at least 3700 times better than the original one, and approximate 980100 in practice on our depth frames. The results conducted on frames demonstrate that the distance from the camera to objects retrieved is exact enough for indoor robot navigation problems.
{"title":"Improved Interval Type-2 Fuzzy Subtractive Clustering for obstacle detection of robot vision from stream of Depth Camera","authors":"Mau Uyen Nguyen, L. Ngo, Dao Thanh Tinh","doi":"10.1109/ISDA.2012.6416658","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416658","url":null,"abstract":"Obstacle detection is a fundamental issue of robot navigation and there have been several proposed methods for this problem. In this paper, we propose a new approach to find out obstacles on Depth Camera streams. The proposed approach consists of three stages. First, preprocessing stage is for noise removal. Second, different depths in a frame are clustered based on the Interval Type-2 Fuzzy Subtractive Clustering algorithm. Third, the objects of interest are detected from the obtained clusters. Beside that, it gives an improvement in the Interval Type-2 Fuzzy Subtractive Clustering algorithm to reduce the time consuming. In theory, it is at least 3700 times better than the original one, and approximate 980100 in practice on our depth frames. The results conducted on frames demonstrate that the distance from the camera to objects retrieved is exact enough for indoor robot navigation problems.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122720366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416662
Tae-Seon Kim, Soo-Won Kim
This paper presents a method for reducing a bumblebee noise generated by a GSM technology in a smartphone. Global smartphone penetration has been very swift and 2nd generation, 3rd generation and 4th generation communication technology are commercially used in the world. The 2nd generation wireless telephone technology is based on two standards, depending on the type of multiplexing used the Global System for Mobile Communication (GSM) and Code-Division Multiple Access (CDMA). In particular, the GSM technology has a market share of almost more than 79% in the world. GSM technology uses a channel access method that combines frequency division multiple access (FDMA) and time division multiple access (TDMA). There are four commercial frequency bands. GSM technology has a burst structure by a TDMA method. And hence, the GSM technology has a disadvantage; radiation noise is generated from an antenna propagation signal of the smartphone, and consequently, the voice quality of the smartphone is degraded. This noise is commonly known as bumblebee noise, buzz noise or TDMA noise. There have been several studies to reduce the noise since a release of GSM technology in a commercial market. Those studies mainly focused on designing infinite impulse response (IIR) notch filters by the signal processing technology or on data burst transmission schemes. The first method needs more million instructions per second (MIPS) for operation, and hence, current consumption increases accordingly. The latter method requires a change in the protocol standard of the GSM; hence, its feasibility is low. This paper presents hardware filters designed to reduce the bumblebee noise in smartphones, especially the bumblebee noise in the headset mode during calls. The bumblebee noise is easily generated in the headset mode of smartphones during calls because the headset is necessarily connected to the smartphone. This paper verified that, on an average the bumblebee noise was reduced up to 14dBm by experiments.
{"title":"A method for reducing a bumblebee noise generated by a GSM technology in a smartphone","authors":"Tae-Seon Kim, Soo-Won Kim","doi":"10.1109/ISDA.2012.6416662","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416662","url":null,"abstract":"This paper presents a method for reducing a bumblebee noise generated by a GSM technology in a smartphone. Global smartphone penetration has been very swift and 2nd generation, 3rd generation and 4th generation communication technology are commercially used in the world. The 2nd generation wireless telephone technology is based on two standards, depending on the type of multiplexing used the Global System for Mobile Communication (GSM) and Code-Division Multiple Access (CDMA). In particular, the GSM technology has a market share of almost more than 79% in the world. GSM technology uses a channel access method that combines frequency division multiple access (FDMA) and time division multiple access (TDMA). There are four commercial frequency bands. GSM technology has a burst structure by a TDMA method. And hence, the GSM technology has a disadvantage; radiation noise is generated from an antenna propagation signal of the smartphone, and consequently, the voice quality of the smartphone is degraded. This noise is commonly known as bumblebee noise, buzz noise or TDMA noise. There have been several studies to reduce the noise since a release of GSM technology in a commercial market. Those studies mainly focused on designing infinite impulse response (IIR) notch filters by the signal processing technology or on data burst transmission schemes. The first method needs more million instructions per second (MIPS) for operation, and hence, current consumption increases accordingly. The latter method requires a change in the protocol standard of the GSM; hence, its feasibility is low. This paper presents hardware filters designed to reduce the bumblebee noise in smartphones, especially the bumblebee noise in the headset mode during calls. The bumblebee noise is easily generated in the headset mode of smartphones during calls because the headset is necessarily connected to the smartphone. This paper verified that, on an average the bumblebee noise was reduced up to 14dBm by experiments.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"618 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123207441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416522
A. Sumathi, R. Vidhyapriya
Cognitive radio is a new technology which compliments the wireless devices by improving the efficiency, speed and reliability. There is always a huge demand for the spectrum usage as the availability of the radio spectrum is limited. Cognitive radio technology is seen as a potential solution to the efficient utilization of available spectrum by the unlicensed legitimate users. One of the major threats of cognitive radio network is the Primary User Emulation attack. In this paper a survey of Cognitive Radio techniques with its IEEE 802.22 standard, various defensive methods against PUE attack, primary signal detection methods and the features of SpiderRadio, a cognitive radio device are presented.
{"title":"Security in cognitive radio networks - a survey","authors":"A. Sumathi, R. Vidhyapriya","doi":"10.1109/ISDA.2012.6416522","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416522","url":null,"abstract":"Cognitive radio is a new technology which compliments the wireless devices by improving the efficiency, speed and reliability. There is always a huge demand for the spectrum usage as the availability of the radio spectrum is limited. Cognitive radio technology is seen as a potential solution to the efficient utilization of available spectrum by the unlicensed legitimate users. One of the major threats of cognitive radio network is the Primary User Emulation attack. In this paper a survey of Cognitive Radio techniques with its IEEE 802.22 standard, various defensive methods against PUE attack, primary signal detection methods and the features of SpiderRadio, a cognitive radio device are presented.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130354934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416582
Ahmed Hafez, N. Ghali, A. Hassanien, A. Fahmy
Community detection in complex networks has attracted a lot of attention in recent years. Community detection can be viewed as an optimization problem, in which an objective function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. Many single-objective optimization techniques have been used to solve the problem however those approaches have its drawbacks since they try optimizing one objective function and this results to a solution with a particular community structure property. More recently researchers viewed the problem as a multi-objective optimization problem and many approaches have been proposed to solve it. However which objective functions could be used with each other is still under debated since many objective functions have been proposed over the past years and in somehow most of them are similar in definition. In this paper we use Genetic Algorithm (GA) as an effective optimization technique to solve the community detection problem as a single-objective and multi-objective problem, we use the most popular objectives proposed over the past years, and we show how those objective correlate with each other, and their performances when they are used in the single-objective Genetic Algorithm and the Multi-Objective Genetic Algorithm and the community structure properties they tend to produce.
{"title":"Genetic Algorithms for community detection in social networks","authors":"Ahmed Hafez, N. Ghali, A. Hassanien, A. Fahmy","doi":"10.1109/ISDA.2012.6416582","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416582","url":null,"abstract":"Community detection in complex networks has attracted a lot of attention in recent years. Community detection can be viewed as an optimization problem, in which an objective function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. Many single-objective optimization techniques have been used to solve the problem however those approaches have its drawbacks since they try optimizing one objective function and this results to a solution with a particular community structure property. More recently researchers viewed the problem as a multi-objective optimization problem and many approaches have been proposed to solve it. However which objective functions could be used with each other is still under debated since many objective functions have been proposed over the past years and in somehow most of them are similar in definition. In this paper we use Genetic Algorithm (GA) as an effective optimization technique to solve the community detection problem as a single-objective and multi-objective problem, we use the most popular objectives proposed over the past years, and we show how those objective correlate with each other, and their performances when they are used in the single-objective Genetic Algorithm and the Multi-Objective Genetic Algorithm and the community structure properties they tend to produce.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130385452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416671
A. Gopalai, S. M. N. Arosha Senanayake, K. Lim
Biofeedbacks delivery during rehabilitation have been known to improve postural control and shorten rehabilitation periods. A biofeedback system communicates with the human central nervous system (CNS) through a variety of feedback modalities. Among the many available modalities vibrotactile feedback devices are gaining much attention. This is due to their desirable characteristics and simplistic manner of presenting information to the CNS. An intelligent biofeedback system integrated with wireless sensors for monitoring postural control during rehabilitation was hypothesized to shorten rehabilitation periods. This work presents the design of a postural control measuring device integrated with real-time intelligent biofeedback for postural correction. The system integrates three modules: (a) inertial measurement units (IMUs), (b) fuzzy knowledge base, and (c) feedback driver circuit. Human posture is measured using Euler angular measurements from the IMUs. A fuzzy inference system (FIS) was used to determine quality of postural control, based on measurements from the IMUs. Forewarning of poor postural control is given by vibrotactile actuators (biofeedback). Experiments were conducted to test viability of the system in achieving accurate real-time measurements and interventions. The results observed improvements in postural control when biofeedback intervention was present.
{"title":"Intelligent vibrotactile biofeedback system for real-time postural correction on perturbed surfaces","authors":"A. Gopalai, S. M. N. Arosha Senanayake, K. Lim","doi":"10.1109/ISDA.2012.6416671","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416671","url":null,"abstract":"Biofeedbacks delivery during rehabilitation have been known to improve postural control and shorten rehabilitation periods. A biofeedback system communicates with the human central nervous system (CNS) through a variety of feedback modalities. Among the many available modalities vibrotactile feedback devices are gaining much attention. This is due to their desirable characteristics and simplistic manner of presenting information to the CNS. An intelligent biofeedback system integrated with wireless sensors for monitoring postural control during rehabilitation was hypothesized to shorten rehabilitation periods. This work presents the design of a postural control measuring device integrated with real-time intelligent biofeedback for postural correction. The system integrates three modules: (a) inertial measurement units (IMUs), (b) fuzzy knowledge base, and (c) feedback driver circuit. Human posture is measured using Euler angular measurements from the IMUs. A fuzzy inference system (FIS) was used to determine quality of postural control, based on measurements from the IMUs. Forewarning of poor postural control is given by vibrotactile actuators (biofeedback). Experiments were conducted to test viability of the system in achieving accurate real-time measurements and interventions. The results observed improvements in postural control when biofeedback intervention was present.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"28 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120866317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416549
M. Lavanya, R. Revathi, J. Rajesh, S. M. Basha
Renewable energy is obtained from various natural processes such as heat generated by sun. Solar energy fluctuates with the intensity of the radiated light. As a result the output power of the panel varies. This varying supply can neither be connected to grid nor used for load. Hence to obtain a constant power, maximum power point technology (MPPT) is adopted. Existing algorithms like Perturb and Observe technique and Incremental Conductance proved to be less efficient in finding the optimal solution. Hence soft computing technique called seeker optimization algorithm is proposed to find the maximum power point. The proposed MPPT control algorithm is developed in MATLAB, which optimizes the PV panel voltage. Generated solar energy usually requires conversion to an alternating quantity, which requires the use of inverters. A seven level inverter is implemented to obtain a harmonic less AC output. Experimental results show that the proposed algorithm proves to be more efficient than the existing techniques.
{"title":"Efficiency enhancement of PV panel using soft computing based seeker optimization algorithm and seven level inverter configuration","authors":"M. Lavanya, R. Revathi, J. Rajesh, S. M. Basha","doi":"10.1109/ISDA.2012.6416549","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416549","url":null,"abstract":"Renewable energy is obtained from various natural processes such as heat generated by sun. Solar energy fluctuates with the intensity of the radiated light. As a result the output power of the panel varies. This varying supply can neither be connected to grid nor used for load. Hence to obtain a constant power, maximum power point technology (MPPT) is adopted. Existing algorithms like Perturb and Observe technique and Incremental Conductance proved to be less efficient in finding the optimal solution. Hence soft computing technique called seeker optimization algorithm is proposed to find the maximum power point. The proposed MPPT control algorithm is developed in MATLAB, which optimizes the PV panel voltage. Generated solar energy usually requires conversion to an alternating quantity, which requires the use of inverters. A seven level inverter is implemented to obtain a harmonic less AC output. Experimental results show that the proposed algorithm proves to be more efficient than the existing techniques.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116444453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416544
Sruthy Mamadhan, T. Manesh, V. Paul
Web applications are becoming an important part of our daily life. So attacks against them also increases rapidly. Of these attacks, a major role is held by SQL injection attacks (SQLIA). This paper proposes a new method for preventing SQL injection attacks in JSP web applications. The basic idea is to check before execution, the intended structure of the SQL query. For this we use semantic comparison. This method prevents different kinds of injection attacks including stored procedure attack which is more difficult and less considered in the literature.
{"title":"SQLStor: Blockage of stored procedure SQL injection attack using dynamic query structure validation","authors":"Sruthy Mamadhan, T. Manesh, V. Paul","doi":"10.1109/ISDA.2012.6416544","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416544","url":null,"abstract":"Web applications are becoming an important part of our daily life. So attacks against them also increases rapidly. Of these attacks, a major role is held by SQL injection attacks (SQLIA). This paper proposes a new method for preventing SQL injection attacks in JSP web applications. The basic idea is to check before execution, the intended structure of the SQL query. For this we use semantic comparison. This method prevents different kinds of injection attacks including stored procedure attack which is more difficult and less considered in the literature.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134208498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416635
R. Jayashree, K. S. Murthy, B. Anami
The growth of internet has given rise to the need for better Information Retrieval (IR) techniques which help in obtaining relevant information at a faster rate. Text Summarization is one such technique which aims at producing a quick and concise summary of the Text. Of late, Key word based summary has drawn wide attention of researchers in Natural Language Processing community. The algorithm we have developed extracts key words from Kannada text documents, for which we combine GSS (Galavotti, Sebastiani, Simi)[13] coefficients and IDF(Inverse Document Frequency) methods along with TF(Term Frequency) for extracting key words and later uses these for summarization. The important objective our work is to assign a weight to each word in a sentence, the weight of a sentence is the sum of weights of all words, based on the scoring of sentences; we choose top `m' sentences. A document from a given category is selected from our database custom built for this purpose. The files are obtained from Kannada Webdunia. Kannada Webdunia is a Kannada Portal which offers Political News, Cinema News, Sports news, Shopping and Jokes. Depending on the number of sentences given by the user, a summary is generated. Finally we make comparison of machine generated summary with that of human summary. Yet another objective of this work is to perform feature extraction through removal of stop words. For removing stop words we have presented a novel technique which finds structurally similar words in a document.
{"title":"Categorized Text Document Summarization in the Kannada Language by sentence ranking","authors":"R. Jayashree, K. S. Murthy, B. Anami","doi":"10.1109/ISDA.2012.6416635","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416635","url":null,"abstract":"The growth of internet has given rise to the need for better Information Retrieval (IR) techniques which help in obtaining relevant information at a faster rate. Text Summarization is one such technique which aims at producing a quick and concise summary of the Text. Of late, Key word based summary has drawn wide attention of researchers in Natural Language Processing community. The algorithm we have developed extracts key words from Kannada text documents, for which we combine GSS (Galavotti, Sebastiani, Simi)[13] coefficients and IDF(Inverse Document Frequency) methods along with TF(Term Frequency) for extracting key words and later uses these for summarization. The important objective our work is to assign a weight to each word in a sentence, the weight of a sentence is the sum of weights of all words, based on the scoring of sentences; we choose top `m' sentences. A document from a given category is selected from our database custom built for this purpose. The files are obtained from Kannada Webdunia. Kannada Webdunia is a Kannada Portal which offers Political News, Cinema News, Sports news, Shopping and Jokes. Depending on the number of sentences given by the user, a summary is generated. Finally we make comparison of machine generated summary with that of human summary. Yet another objective of this work is to perform feature extraction through removal of stop words. For removing stop words we have presented a novel technique which finds structurally similar words in a document.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133650967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：