Automatic Summarization & Neural Networks 2015

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Automatic Summarization & Neural Networks 2014

Ranking with Recursive Neural Networks and Its Application to Multi-Document Summarization. Z Cao, F Wei, L Dong, S Li, M Zhou – AAAI, 2015 – … Briefly, RNN pro- cesses structured inputs (usually a binary tree) by repeatedly applying the same neural network at each node. … We take ROUGE-2 recall as the main metric for comparison due to its high capability of evaluating automatic summarization systems (Owczarzak et al … Cited by 29 Related articles All 7 versions

Lcsts: A large scale chinese short text summarization dataset B Hu, Q Chen, F Zhu – arXiv preprint arXiv:1506.05865, 2015 – … 2011. Automatic summarization. Foundations and Trend in Information Retrieval, 5(2-3):103–233. … 2014. Sequence to sequence learning with neural networks. In Advances in Neu- ral Information Processing Systems 27, pages 3104– 3112. [Zeiler2012] Matthew D. Zeiler. … Cited by 16 Related articles All 14 versions

Extractive broadcast news summarization leveraging recurrent neural network language modeling techniques KY Chen, SH Liu, B Chen, HM Wang, EE Jan… – IEEE/ACM Transactions …, 2015 – … Leveraging Recurrent Neural Network Language Modeling Techniques … In view of this, our work in this paper explores a novel use of recurrent neural network language modeling (RNNLM) framework for extractive broadcast news summarization. … Cited by 7 Related articles All 12 versions

Summarization-based video caption via deep neural networks G Li, S Ma, Y Han – Proceedings of the 23rd ACM international …, 2015 – … C- NN), which are then fed into a Recurrent Neural Networks (RN- N) to generate novel sentences descriptions for each frame. In or- der to obtain the most representative and high-quality descriptions for target video, a well-devised automatic summarization process is … Cited by 4 Related articles

Beyond the hype: Big data concepts, methods, and analytics A Gandomi, M Haider – International Journal of Information Management, 2015 – Elsevier … predictions. Based on the underlying methodology, techniques can also be categorized into two groups: regression techniques (eg, multinomial logit models) and machine learning techniques (eg, neural networks). Another … Cited by 244 Related articles All 4 versions

Learning Summary Prior Representation for Extractive Summarization. Z Cao, F Wei, S Li, W Li, M Zhou, H Wang – ACL (2), 2015 – … In Proceedings of ACL Work- shop on Automatic Summarization, pages 1–8. Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Grégoire Mesnil. 2014. Learning semantic rep- resentations using convolutional neural networks for web search. … Cited by 11 Related articles All 11 versions

SemEval-2015 Task 1: Paraphrase and semantic similarity in Twitter (PIT) W Xu, C Callison-Burch… – Proceedings of SemEval, 2015 – … 4.4 Automatic Summarization Inspired Sentence Filtering We filter the sentences within each topic to se- lect more probable paraphrases for annotation. … About half of systems use word embeddings and many use neural networks. … Cited by 35 Related articles All 17 versions

Natural language inference by tree-based convolution and heuristic matching L Mou, R Men, G Li, Y Xu, L Zhang, R Yan… – arXiv preprint arXiv: …, 2015 – … standing and has wide applications in NLP, eg, question answering (Harabagiu and Hickl, 2006) and automatic summarization (Lacatusu … The renewed prosperity of neural networks has made significant achievements in various NLP ap- plications, including individual sentence … Cited by 14 Related articles All 6 versions

Automatic text summarization of Wikipedia articles D Hingu, D Shah, SS Udmale – Communication, Information & …, 2015 – … The scores are used to classify the sentence to be in the summary text or not with the help of a neural network. … The objective of automatic text summarization (automatic summarization/text summarization) is the reduction of a given text to a smaller number of sentences without … Cited by 3 Related articles All 2 versions

Query-oriented unsupervised multi-document summarization via deep learning model S Zhong, Y Liu, B Li, J Long – Expert Systems with Applications, 2015 – Elsevier … Back propagation, a well-known computationally efficient model for multilayer neural networks, also suffers from insufficient labeled data, high computational cost, and poor local optima when working under a deep model (Hinton, 2007). … Cited by 9 Related articles All 5 versions

Short text similarity with word embeddings T Kenter, M de Rijke – Proceedings of the 24th ACM International on …, 2015 – … successfully is beneficial in many settings in information retrieval like search [26], query suggestion [30], automatic summarization [3] and … Recent developments in distributional semantics, in particular neural network-based approaches like [32, 34] only require a large amount of … Cited by 30 Related articles All 9 versions

Improving Performance of Text Summarization SA Babar, PD Patil – Procedia Computer Science, 2015 – Elsevier … The automatic summarization means an automatically summarized output is given when an input is applied. … Hidden Markov models and log-linear models are used to improve extractive summarization Now a day’s neural networks are used to generate summary for single … Cited by 7 Related articles All 3 versions

Recognizing entailment and contradiction by tree-based convolution L Mou, R Men, G Li, Y Xu… – CoRR, abs/ …, 2015 – … In our previ- ous work, the tree-based convolutional neural network (TBCNN) has achieved high perfor- mance in several sentence-level classification tasks. … question answering (Harabagiu and Hickl, 2006), automatic summarization (Lacatusu et al., 2006), etc. … Cited by 13 Related articles All 4 versions

The automatic summarization of text documents in the Cognitive Integrated Management Information System M Hernes, M Maleszka, NT Nguyen… – Computer Science …, 2015 – … RELATED WORKS The problems of automatic summarization have been widely considered in many papers and practical solutions. … algorithms) or converting knowledge into numerical representation followed by numerical processing (eg with the use of neural networks or fuzzy … Cited by 4 Related articles All 4 versions

System Combination for Multi-document Summarization. K Hong, M Marcus, A Nenkova – EMNLP, 2015 – … 2014)) on the DUC 04 data. On the DUC 01 and 02 data, the top performing systems we find are R2N2 ILP (Cao et al., 2015a) and PriorSum (Cao et al., 2015b); both of them utilize neural networks. Comparing to these two, Cited by 8 Related articles All 12 versions

Emerging directions in predictive text mining N Indurkhya – Wiley Interdisciplinary Reviews: Data Mining and …, 2015 – Wiley Online Library … The first is a multilayer network in which the hidden layers encode the hierarchical representations.[4] The other type of representation is a recurrent neural network that can represent complex patterns that depend on context length.[13] While the … AUTOMATIC … Cited by 5 Related articles All 4 versions

Multi-document extractive summarization using window-based sentence representation Y Zhang, MJ Er, R Zhao – Computational Intelligence, 2015 …, 2015 – … [30] for a single-hidden-layer feedforward neural network (SLFN) with randomly chosen input weights and hidden nodes and analytically determined output weights. … We adopt the widely-accepted automatic summarization evaluation metric, ROUGE, to measure the salience. … Cited by 3 Related articles All 3 versions

Tgsum: Build tweet guided multi-document summarization dataset Z Cao, C Chen, W Li, S Li, F Wei, M Zhou – arXiv preprint arXiv: …, 2015 – … Introduction The rapid growth of on-line digital content calls for effi- cient automatic summarization systems. … [Cao et al. 2015a] Cao, Z.; Wei, F.; Dong, L.; Li, S.; and Zhou, M. 2015a. Ranking with recursive neural networks and its application to multi-document summarization. … Cited by 5 Related articles All 9 versions

An overview of graph-based keyword extraction methods and approaches S Beliga, A Meštrovi?, S Martin?i?-Ipši? – Journal of information and …, 2015 – … of the document is also the task of many IR and NLP applications and includes automatic indexing, automatic summarization, document management … and the frequency appearing in the paragraphs of the given document in the combination with Neural Networks are proposed. … Cited by 10 Related articles All 11 versions

Leveraging word embeddings for spoken document summarization KY Chen, SH Liu, HM Wang, B Chen… – arXiv preprint arXiv: …, 2015 – … The central idea of these methods is to learn continuously distributed vector representations of words using neural networks, which can probe latent semantic and/or syntactic cues that can in turn be used to induce similarity measures among words, sentences, and documents. … Cited by 3 Related articles All 8 versions

Automatic summarization of polish news articles by sentence selection K Jassem, ? Pawluczuk – Computer Science and Information …, 2015 – … Ogrodniczuk and Kopec notice that previous works on automatic summarization in the Polish language lacked a common corpus and a common evaluation method, therefore their results … The summarization component appplies neural networks as a machine learning algorithm. … Cited by 2 Related articles All 7 versions

Automatic text document summarization based on machine learning G Silva, R Ferreira, RD Lins, L Cabral… – Proceedings of the …, 2015 – … 4. CONCLUSIONS AND LINES FOR FUR- THER WORKS Automatic summarization opens a wide number of possi- bilities such as the efficient classification, retrieval and in- formation based compression of text documents. … Neural Networks: A Comprehensive Foundation. … Cited by 4 Related articles All 2 versions

Incorporating paragraph embeddings and density peaks clustering for spoken document summarization KY Chen, KW Shih, SH Liu, B Chen… – … (ASRU), 2015 IEEE …, 2015 – … 1. Illustrations of (a) the feed-forward neural network language model (NNLM), (b) the distributed memory model (DM), and (c) the … Maximum margin relevance (MMR) is the most popularly used criterion for automatic summarization [23], based on which redundancy is computed … Cited by 2 Related articles All 2 versions

Exploring actor–object relationships for query-focused multi-document summarization M Valizadeh, P Brazdil – Soft Computing, 2015 – Springer … The MATLAB implementations were used. The neural network 3 used had 2 hidden layers and 10 nodes per each layer. … Automatic evaluation toolkit (ie, ROUGE-1.5.5) that is the state-of-the-art of automatic summarization evaluation based on N-gram comparison was used. … Cited by 3 Related articles All 4 versions

Query-based single document summarization using an ensemble noisy auto-encoder MY Azar, K Sirts, DM Aliod, L Hamey – … Association Workshop 2015, 2015 – … 2 Background Automatic summarization can be categorized into two distinct classes: abstractive and extractive. … There has been some previous work on using deep neural networks for automatic text summa- rization. The most similar to our work is the model by Zhong et al. … Cited by 2 Related articles All 12 versions

How well sentence embeddings capture meaning L White, R Togneri, W Liu, M Bennamoun – Proceedings of the 20th …, 2015 – … For applications where encoding semantic meaning is particu- larly desirable, such as machine translation and automatic summarization, it is … It functions by recursively using a single layer feedforward neural-network to combine embed- ded representations, following the parse … Cited by 4 Related articles All 2 versions

Dimensionality on summarization H Zhuge – arXiv preprint arXiv:1507.00209, 2015 – … (3) Closed system. The process of automatic summarization is closed, does not interact with other processes in cyberspace or social space. … Natural Language Analysis Synthesized Extractive Bayes Decision Tree Hidden Markov Neural network Evaluation Human Automatic … Cited by 5 Related articles All 2 versions

Domain independent framework for automatic text summarization YK Meena, D Gopalani – Procedia Computer Science, 2015 – Elsevier … 11] in 2009 proposed trainable models genetic algorithm, mathematical regression, feed forward neural networks, probabilistic neural network and Gaussian … single and multi-document summaries with GISTEXTER,” Proceedings of the workshop on automatic summarization, pp … Cited by 2 Related articles All 2 versions

A supervised approach to arabic text summarization using adaboost R Belkebir, A Guessoum – New Contributions in Information Systems and …, 2015 – Springer … In [7] a compar- ative study between three approaches for automatic summarization of Arabic documents is presented. … Then, they used a combination of all the features to train the probabilistic neural network (PNN) so as to generate a text summarizer. … Cited by 2 Related articles All 2 versions

A study on the use of word embeddings and pagerank for vietnamese text summarization V Phung, L De Vine – Proceedings of the 20th Australasian Document …, 2015 – … 2. RELATED WORKS Automatic summarization has captured the attention of many experts, and it has resulted in many different ap … such as Bayes, Hidden Markov Model (HMM), Latent Dirichlet Allocation (LDA), Support Vector Machine (SVM) or neural networks to solve the … Cited by 2 Related articles All 2 versions

A Review of Text Mining Techniques Associated with Various Application Areas DS Dang, PH Ahmad – International Journal of Science and Research (IJSR), 2015 – … Image collection summarization is other application example of automatic summarization [13], [15], [18]. 2.4 Text Categorization … Automatic: Typically exploiting machine learning techniques • Vector space model based • Prototype-based (Rocchio) • Neural Networks (learn non … Cited by 2 Related articles All 2 versions

Named Entity Recognition system for Hindi Language using combination of rule based approach and list look up approach Y Kaur, E Kaur – International Journal of scientific research and …, 2015 – … Connectionist approaches also recovered from earlier criticism by demonstrating the utility of neural networks in NLP. … Information Extraction • Automatic summarization • Machine translation • Named entity recognition (NER) Page 2. … Cited by 3 Related articles All 2 versions

A Review on Text Similarity Technique used in IR and its Application N Pradhan, M Gyanchandani… – International Journal of …, 2015 – … Rudi Cilibrasi, Paul MB Vitanyi, Normalized Web distance and word similarity, in NAACL-ANLP Workshop on Automatic summarization, May 2009. … has around 15 years of teaching experience and her area of interest includes Artificial Intelligence, Neural Networks and Intrusion … Cited by 4 Related articles All 4 versions

Positional language modeling for extractive broadcast news speech summarization. SH Liu, KY Chen, B Chen, HM Wang, HC Yen… – …, 2015 – … As to future work, we envisage to leverage more sophisticated language models, such as the long short-term memory (LSTM) neural network and its variants [36, 37], to jointly integrating more proximity and different kinds of acoustic and lexical information, as well as discourse … Cited by 2 Related articles All 6 versions

Literature Review on Automatic Text Summarization: Single and Multiple Summarizations N Bhatia, A Jaiswal – International Journal of Computer …, 2015 – … HP Luhn was the first one who invented automatic summarization of text in 1958 [24]. NLP community invented the subfield of summarization. … Neural Networks [6]: Due to its outperforming statistical significance, neural network overcome the problem of extractive summarization. … Cited by 1 Related articles All 4 versions

Arabic Documents Classification Method a Step towards Efficient Documents Summarization HA Hassan, M YehiaDahab, K Bahnassy… – International Journal on …, 2015 – … a successful framework for agricultural documents classification as a step forward for a language independent automatic summarization approach. … An example of these classifiers are neural networks [7], support vector machines [8], genetic programming [9], Various of these … Cited by 1 Related articles All 4 versions

Optimal Features Set for Extractive Automatic Text Summarization YK Meena, P Dewaliya… – Advanced Computing & …, 2015 – … Automatic summarization can be classified as extractive and abstractive summarization. … Fattah and Ren 2009 [6] proposed trainable models genetic algorithm, mathematical regression, feed forward neural networks, probabilistic neural network and Gaussian mixture model for … Cited by 1 Related articles All 4 versions

Learning language-independent sentence representations for multi-lingual, multi-document summarization G Balikas, MR Amini – 17ème Conférence Francophone sur l’ …, 2015 – … Page 3. duced by Hinton [10] where one relies on a neural network to discover features that characterize the meaning of a concept. … Apart from the word embeddings, the input of the Neural Networks in- cludes a token for the text-span to which the words belong to. … Cited by 1 Related articles All 2 versions

Automatic Multi-Document Arabic Text Summarization Using Clustering and Keyphrase Extraction, 1–9 HN Fejer, N Omar – Journal of Artificial Intelligence, 2015 – … Research on automatic summarization of Arabic-language documents has started approximately 10 years ago (Conroy et al., 2006; Douzidia … a wide number of different fields including text mining, information retrieval and machine learning of neural network, pattern recognition … Cited by 1 Related articles All 3 versions

[BOOK] Multimedia, Communication and Computing Application: Proceedings of the 2014 International Conference on Multimedia, Communication and Computing … A Leung – 2015 – … Wang & Z. Chai pll-based adaptive power line interference canceller for eCg signal TJ Li & TH Li Study on fuzzy neural network controller for … for i/o functions in automatic test YW Yang, YW Wang & YZ Gong Multi-features based classification for automatic summarization HY Li … Cited by 1 Related articles All 3 versions

Discovering Subtle Word Relations in Large German Corpora S Buschjäger, L Pfahler, K Morik – Challenges in the …, 2015 – … complexity of their model, the authors enable the efficient use of large text corpora resulting in a simple neural network with input … nition (Turian et al., 2009), Machine Translation (Zou et al., 2013), Sentiment Analysis (Maas et al., 2011) or Automatic Summarization (Kage- back … Cited by 1 Related articles All 5 versions

Document summarization and evaluation using knowledge based super set features S Garg, S Chhillar – International Journal of Computer …, 2015 – … Neural network technique is used for summary extraction of science and social subjects in the educational text. [6]. … Published by Elsevier BV. [12] Tiedan Zhu, Kan Li, The Similarity Measure Based on LDA for Automatic Summarization, 2011 Published by Elsevier Ltd. 10. … Cited by 1 Related articles All 6 versions

Extractive Single-Document Summarization Based on Global-Best Harmony Search and a Greedy Local Optimizer M Mendoza, C Cobos, E León – Mexican International Conference on …, 2015 – Springer … Automatic summarization is an area that has explored different methods for the automatic generation of single document summaries, such as (1 … 4]; (2) Machine learning approaches, including Bayes’ Theorem [5, 6], Hidden Markov Models [7, 8], Neural networks [9], Conditional … Cited by 1 Related articles

A New Biomimetic Method Based on the Power Saves of Social Bees for Automatic Summaries of Texts by Extraction MA Boudia, RM Hamou, A Amine… – International Journal of …, 2015 – … Our current work uses automatic summarization by extraction as it is a simple method to implement that gives good results; only in the previous work, produce the automatic summary by extraction approach consists to use only one technique at a time (Scoring of phrase, Similar … Cited by 1 Related articles All 2 versions

Automatic summarization of soccer highlights using audio-visual descriptors A Raventos, R Quijada, L Torres, F Tarrés – SpringerPlus, 2015 – Springer … Abstract. Automatic summarization generation of sports video content has been object of great interest for many years. … Afterwards, the system applies a support vector machine and an artificial neural network algorithm for emphasizing important segments with logo appearance. … Cited by 1 Related articles All 15 versions

The sensei project: Making sense of human conversations G Riccardi, F Bechet, M Danieli, B Favre… – … Workshop on Future …, 2015 – Springer … This is the approach followed in SENSEI. Deep Neural Network Models. Recent … corpus. A comparison of CRF and Neural Network methods is given in Fig. 2 for the semantic frame tagging task on the SENSEI call-centre corpus. … Cited by 1 Related articles All 9 versions

Automatic summarization of risk factors preceding disease progression an insight-driven healthcare service case study on using medical records of diabetic patients PYS Hsueh, XX Zhu, MJH Hsiao, SYF Lee, V Deng… – World Wide Web, 2015 – Springer Page 1. Automatic summarization of risk factors preceding disease progression an insight-driven healthcare service case study on using medical records of diabetic patients Pei-Yun S. Hsueh & Xin Xin Zhu & Mark JH Hsiao … Cited by 1 Related articles All 5 versions

PSO-Based Feature Selection for Arabic Text Summarization. AM Al-Zahrani, H Mathkour, HI Abdalla – J. UCS, 2015 – … The two broad classes of automatic summarization are extractive and abstractive [Das, 2007]. … [Kennedy, 1995] Kennedy J. and Eberhart R. Particle swarm optimization [Journal] // Proceedings of the IEEE International Conference on Neural Networks, Australia,: [sn], 95. PP. … Cited by 1 Related articles All 6 versions

Semi-automatic construction of a textual entailment dataset: selecting candidates with Vector Space Models ER Fonseca, SM Aluisio – Brazilian Symposium in Information …, 2015 – … More related to our process, in the Automatic Summarization task, annotators examined the summary of a news cluster and selected sentences (outside the summary) with … In recent years, new kinds of VSMs based on neural networks have emerged in NLP [Pennington et al. … Cited by 1 Related articles All 6 versions

TR-LDA: A Cascaded Key-Bigram Extractor for Microblog Summarization Y Wu, H Zhang, B Xu, H Hao… – International Journal of …, 2015 – … [22] U. Hahn and I. Mani, The challenges of automatic summarization, Computer, vol. … His research interests include pattern recognition, image processing, neural networks, machine learning, and especially the applications to character recognition and document analysis. … Cited by 1 Related articles All 2 versions

Big data analytics techniques: A survey P Vashisht, V Gupta – Green Computing and Internet of Things ( …, 2015 – … patterns and capture relationships in the data and is categorized in two ways: regression techniques (eg multinomial logic models) and machine learning techniques (eg neural networks).Predictive analytics … “The challenges of automatic summarization.” Computer 33.11 ( … Cited by 1 Related articles All 3 versions

Classifying informative and imaginative prose using complex networks HF de Arruda, LF Costa, DR Amancio – arXiv preprint arXiv:1507.07826, 2015 – … The application of such techniques have allowed an improvement of several linguistic applications, which encompasses machine translation, automatic summarization and document classification. … not hidden from the user, as it happens in artificial neural networks methods [64]. … Cited by 1 Related articles All 4 versions

Design and Development of an Automatic Text Summarization Using Pragmatic-Enabled Features with LMS based Neural network CS Kameswari, JA Chandulal – 2015 – … Keywords: pragmatic analysis, LMS based neural network, WorldNet, feature 1. INTRODUCTION … By extracting the quintessence of data, the automatic summarization lends a helping hand to the humans to tackle the enormity of the data. … Related articles All 2 versions

Automatic Document Summarization via Deep Neural Networks C Yao, J Shen, G Chen – Computational Intelligence and …, 2015 – … Topics in Cognitive Science, 2010. [7] Krizhevsky A., Sutskever I., Hinton GE ImageNet Classification with Deep Convolutional Neural Networks. … In Proceedings of the ACL’02 Workshop on Automatic Summarization, pages 1-8, Morristown, NJ, USA. 2002. … Related articles

A Comparative Study Of Hindi Text Summarization Techniques: Genetic Algorithm And Neural Network PG Student, DM COE – 2015 – … We are proposing two machine learning techniques Genetic Algorithm (GA) and Artificial Neural Network (ANN) for the sentence extraction and ranking. … n. So for people who do not know English but want to read articles on the Internet, automatic summarization would play lion … Related articles

Document Summarization Using Sentence Features R Rautray, RC Balabantaray… – International Journal of …, 2015 – … 4. Save the output of the functional link- based neural network for each sentence (the output is a value of 0 or 1). 5. Select sentences of class-1 chronologically from the document … In this paper, investigation of extractive feature based automatic summarization task is carried out. … Related articles All 3 versions

A Survey to Automatic Summarization Techniques P Bhatia – … Multilingual text summarization is a new research area in automatic summarization. A little work has been done in this research area. Mostly UNL is used for language translation. … Machine learning includes naïve Bayes, decision trees, and neural networks. … Related articles All 2 versions

CS224d Project Final Report E Chai, N Gallagher – work – … Abstract We develop a Recurrent Neural Network (RNN) Language Model to extract sen- tences from Yelp Review Data for the purpose of automatic summarization. We compare these extracted sentences against user-generated … Related articles All 4 versions

Natural Language Generation, Paraphrasing and Summarization of User Reviews with Recurrent Neural Networks – … We demonstrate practical application of our system on the task of multiple consumer reviews summarization. Keywords: natural language generation, paraphrase generation, automatic summarization of user reviews, recurrent neural networks 1. Introduction … Related articles

Analysis On Extractive Automatic Text Summarization Using Machine Learning N Preethi – … This straight forward definition captures 3 necessary aspects that characterize analysis on automatic summarization: … E. Neural Networks and Third Party Features In 2001-02, DUC issued a task of creating a 100-word summary of a single news article. … Related articles

Learning Sentence Vector Representations to Summarize Yelp Reviews N Khosla, V Venkataraman – 2015 – … We also culled out stop words for the Bag of Words models, but not for the neural network based models. … The canonical metric used to evaluate automatic summarization is ROUGE, which stands for Recall- Oriented Understudy for Gisting Evaluation. … Related articles All 5 versions

The Initial Study of Term Vector Generation Methods for News Summarization M Rott – RASLAN 2015 Recent Advances in Slavonic Natural …, 2015 – … Keywords: Latent Semantic Analysis, Random Manhattan Indexing, Skip-gram Model, Vector Space Model, Automatic Summarization 1 Introduction Two novel methods … gram Model The training of this model is very efficient and is based on log-linear neural network architecture. … Related articles All 2 versions

Summarization of Malayalam Document Using Relevance of Sentences EB Ajmal, RP Haroon – … To classify the sentences in a document as summary sentences and non-summary sentences based on the features that they possess [4]. Nave Bayes method, Neural networks and Hidden Markov Model (HMM … The automatic summarization process may contain following steps. … Related articles

Multilingual Summarization L Wanner – … Amount / Lack of information redundancy in the summary ? … Page 14. (Very) coarse-grained time line of automatic summarization ? 50ies – 70ies ? 80ies ? Experimental statistical techniques Exploration of individual distributional features or of a combination … Related articles

A Template Based Algorithm For Automatic Summarization And Dialogue Management For Text Documents PG Desai, H Sarojadevi, NN Chiplunkar – … Laters authors are of the opinion that, neural networks perform better for extracting keywords. … These results indicate that the accuracy of both automatic summarization and dialogue management algorithms is more than70%. … Related articles All 2 versions

Real Time Tweet Summarization and Sentiment Analysis of Game Tournament V Hole, M Takalikar – … NaIve Bayes (NB) and Maximum Entropy (MaxEnt) classifiers are well discussed in many literatures such as Pang and Lee [11][16][17], whereas Artificial Neural Networks (ANN) have … [18] Sharifi Beaux, Mark-Anthony Hutton and Jugal Kalita, “Automatic summarization of twitter … Related articles All 2 versions

Towards an Efficient Approach for Automatic Medical Document Summarization P Gayathri, N Jaisankar – Cybernetics and Information Technologies, 2015 – … The aim of the automatic summarization system is to shorten the length of the document without affecting the overall meaning. … The work presented in [5] exploits an extraction based single document summarization approach, using neural networks and fuzzy logic. … Related articles All 4 versions

A survey of text summarization techniques for sentence extraction R Ahmadi – ACADEMIE ROYALE DES SCIENCES D OUTRE-MER …, 2015 – … NEURAL NETWORKS Feed Forward, a three-layer neural network, is used to implement a system of automatic summarization [27]. In fact, the neural network learns the major paradigms effective for the selection of words in summarizing the text. … Related articles

Facilitating online discussions by automatic summarization S Wubben, S Verberne, EJ Krahmer… – 2015 – … is largely unsupervised, using recurrent neural networks. Evaluation of the first version should point out where in the pipeline supervised techniques and/or heuristics are required to improve our summarization toolbox. If successful, the automatic summarization of discussion … Related articles All 2 versions

A Review On Various Text Mining Techniques And Algorithms R Balamurugan, S Pushpa – … Page 9. 845 | P age • K-Nearest Neighbours • Naïve Bayes • Neural Networks • Association rule-based • Boosting … Model-Based clustering(Neural Network Approach) – clusters are represented by exemplars(eg: SOM) VI. COMPARISON OF TEXT MINING TECHNIQUES … Related articles

Automatic Text Summarization S AJMERA – 2015 – … Page 9. Abbreviations NN – Neural Network FV – Feature Vector v … Accoring to WordNet(Princeton) summary is defined as “a brief statement that presents the main points in a concise form”. Automatic Summarization is a process of generating summaries by a computer program. … Related articles

Soccer Events Summarization by Using Sentiment Analysis S Jai-Andaloussi, I El Mourabit… – Computational …, 2015 – … Doing this, we seek to develop an automatic summarization system which allows to extract relevant information from a large number of … to a spam or not spam label, we used three learning algorithms: SVM (Support Vector Machine), Naive Bayes and neural network proposed by … Related articles All 4 versions

Document summarization based on semantic representations H Zhang, X Zhang, G Gao – Asian Language Processing (IALP), …, 2015 – … And [26] proposed a method to model the sentence as a vector by recurrent neural network, which has long term memory. In future, we can employ these techniques to model the word order and make a better representation for automatic summarization system. … Related articles

Video Text Detection Based on Laplace Transform ZHU Zhijian – Radio & TV Broadcast Engineering, 2015 – … Dianzi University;College of Computer Science and Technology, Zhejiang University;;Text Semantics Based Automatic Summarization for Chinese … 4, Sun Yongke,Zhou Kailai(Southwest Forestry University,Kunming 650224,China);A Neural Network Ensemble Algorithm Based … Related articles

Optimization Of Automatic Highlight Detection For Football Broadcasts T Frensch – 2015 – … reduction of performance is allowed, we have reached a reduction in the number of inputs of up to 40 times. vii Page 8. Contents List of Figures x List of Tables xi 1 Introduction 1 1.1 Automatic Summarization . . . . . … 36 5.5 Neural Network . . . . . … Related articles All 2 versions

A Survey of Text Mining Concepts GR Banu, VK Chitra – … Another disadvantage is that neural networks are extremely difficult to understand for an average user; this may negatively influence the acceptance of these methods. 4. Regression-based Methods … NAACL Workshop Automatic Summarization, pp. 41-49, 2001. … Related articles All 2 versions

Automatic Text Summarization A Rajkhowa – … Naïve-Bayes Methods, Rich Features and Decision Trees, Hidden Markov Models, Log-Linear Models and Neural Networks and Third … Hassel, Koenraad de Smedt, Anja Liseth, Till Christopher Lech and Wedekind, “Porting and Evaluation of Automatic Summarization”, 2003. … Related articles

Arabic Text Summarization Using Latent Semantic Analysis FM Ba-Alwi, GH Gaphari, FN Al-Duqaimi – … Unfortunately, there is a limitation of the algorithm performance, thus any future work should be based on Neural Network, Genetic. 12. … 2012;7(3). 2. Rui Yang, et al. Automatic summarization for Chinese text using affinity propagation clustering and latent semantic analysis. … Related articles All 2 versions

Text Summarization Using Particle Swarm Optimization Algorithm ABDEY MAHJOUB – 2015 – … summary that create by machine is called automatic summarization. The needs for automated … 1-2 Problem Background The need to automatic summarization becomes more important because the large volume of text document information overload. The first work in … Related articles

Image summarization using topic modelling V Sharma, A Kumar, N Agrawal, P Singh… – Signal and Image …, 2015 – … They provide classes of submodular component functions (including some which are instantiated via a deep neural network) over which mixtures may be learnt. … 993–1022, 2003. [3] J. Li, JH Lim, and Q. Tan, “Automatic summarization for personal digital photos,” Information … Related articles

Automatic Microblog Summarization Based on Unsupervised Key-Bigram Extraction Y Wu, H Zhang, B Xu, H Hao… – International Journal of …, 2015 – … Key words: Automatic summarization, key-bigram extraction, microblog, sentence extraction. … His research interests include pattern recognition, image processing, neural networks, machine learning, and especially the applications to character recognition and document analysis … Related articles All 2 versions

Data Mining, an Approach for Developing the Health Domain S Tofighi, A Ghazvini, G Pourtaghi… – … Journal of Medical …, 2015 – … Due to the existence of the large datasets in health-care organizations, data mining process has become necessary towards the automatic summarization of data and the extraction … Keywords: Data Mining, Health, Decision Tree, Neural Networks, Networks, Genetic Algorithms … Related articles All 2 versions

Multilingual Text Summarization PB Bhatia – 2015 – … generate summary. Although text summaries have traditionally focused on text as input, the input to the automatic summarization can be images, multimedia, video or audio as well as hypertext or online information [1]. Due to the increase in the quantity of data … Related articles

Major Research Challenges in Data Mining AN Paidi – … 7 terms Neural Networks are non-linear statistical data modelling tools[5]. They can be used to model complex relationships between input … that go beyond classification and clustering [5]. Some interesting questions include how to perform better automatic summarization of text … Related articles

Disease related knowledge summarization based on deep graph search X Wu, Z Yang, ZH Li, H Lin, J Wang – BioMed research international, 2015 – … developed a web application, called Semantic MEDLINE, which integrates PubMed with natural language processing, automatic summarization, visualization, and interconnections among multiple sources of relevant biomedical information [5]. Several years later, they … Related articles All 13 versions

Testing Methodologies and Exploring Challenges and Issues in Text Summarisation D Patel, H Chhinkaniwala – International Journal of Data Mining …, 2015 – … In [9], the authors have investigated use of genetic algorithm (GA), Mathematical Regression (MR), Feed forward neural network (FFNN) and probabilistic neural network (PNN) to address the problem of improving content selection in text summarisation. … Related articles All 2 versions

Multi-document Arabic Text Summarization KSAL Harazin – 2015 – … legal area, news area and any other fields because it saves time and resources. Automatic summarization is the process of reducing a text document with a computer … quantity of data has increased, so has interest in automatic summarization. Technologies … Related articles

Measuring visual structure in phase and fluorescence microscopy using image compression R Joshi, SR Swaminathan, M Winter, JS Saini… – … [8] DC Ciresan, A. Giusti, LM Gambardella, and J. Schmidhuber, “Mitosis detection in breast cancer histology images with deep neural networks,” Med Image Comput … [11] AR Cohen, C. Bjornsson, S. Temple, G. Banker, and B. Roysam, “Automatic Summarization of Changes in … Related articles

Detection of Outlier Information Using Linguistic Summarization. A Duraj, PS Szczepaniak, J Ochelska-Mierzejewska – FQAS, 2015 – … Using Linguistic Summarization Agnieszka Duraj, Piotr S. Szczepaniak and Joanna Ochelska-Mierzejewska Abstract The main goal of automatic summarization of databases … In: Pro- ceedings of the 5th Conference on Neural Networks and Soft Computing, Zakopane, Poland, … Related articles All 2 versions

Application of Genetic Algorithms to Context-Sensitive Text Mining M HUKa, J MIZERA-PIETRASZKO – Advances in Digital …, 2015 – … Automatic summarization is a way to find out the most popular topics in the text, but still it does not generate a query … MKM Rahman, Multilayer SOM with tree-structured data for efficient document retrieval and plagiarism detection, IEEE Transactions on Neural Networks 20 (2009 … Related articles All 2 versions

A Survey On Custering Sentence-Level Text Using A Novel Fuzzy Relational Clustering Algorithm SS Bere – … NAACL Workshop Automatic Summarization, pp. 41-49, 2001 … 3, No. 2, March 2013 [4] Rui Xu, Student Member, IEEE and Donald Wunsch II, Fellow, IEEE,” Survey of Clustering Algorithms”, IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 16, NO. 3, MAY 2005 … Related articles

Performance Analysis on Text Steganalysis Method Using A Computational Intelligence Approach R Din, SAM Yusof, A Amphawan, HS Hussain… – … Besides, the use of other computational intelligence method such as neural network, fuzzy evaluation, swarm optimization, and … towards multi-document summarization,” ANLP/NAACL Workshops, NAACL-ANLP 2000 Workshop on Automatic Summarization, Seattle, Washington … Related articles

Sentiment Analysis: Approaches, Applications and Challenges S Bhattacharjee, AK Ray – 2015 – … In the literature, opinion mining is thus also referred to as subjectivity classification [5, 7-9]. Automatic summarization of a number … supervised machine learning algorithms have been used for sentiment analysis tasks such as [1]: • Naive Bayes • SVM • MaxEnt • Neural Networks … Related articles

Text Summarization Using Ant Colony Optimization Algorithm OF HASSAN – 2015 – … visualizations strategies. 2-1-5 Automatic Text Summarization System Automatic summarization is the creation of a briefer representation of a body Page 20. 10 … based on sentence extraction approach using neural network for learning combine … Related articles

A computational framework for Tamil document classification using Random Kitchen Sink JP Sanjanasri – Advances in Computing, Communications …, 2015 – … Retrieval is the task of extracting the documents that is appropriate to the search query from within the large collection [2]. Automatic summarization, web searching … K. Rajan, et al used Artificial Neural Network (ANN) and Vector Space Model (VSM) for classifying Tamil texts. … Cited by 1 Related articles All 2 versions

A survey on existing extractive techniques for query-based text summarization N Rahman, B Borah – Advanced Computing and …, 2015 – … Support Vector Machine (SVM), k Nearest Neighbors (kNN), Naive Bayes Classifier, Neural Networks, Decision Trees are some techniques … 1-21. [18] RVVM Krishna, SVP Kumar and CS Reddy, A hybrid method for query based automatic summarization system, International … Related articles All 2 versions

Detecting Terrorism-Related Articles On The E-Government Using Text-Mining Techniques RM Aliguliyev, GY Niftaliyeva – … [1] uses data extraction and clustering methods of text-mining techniques in identifying criminal documents in Arabic. A rules-based approach is applied for data extraction, and a self-organized neural network (Kohonen network) is applied for document clustering. … Related articles

A Rule based Data Mining Mechanism: Association Rule Mining M Malik, RP Agarwal – International Journal of Research in …, 2015 – … 178 statistical, machine learning, and neural networks that mine the data in various ways. … These needs are automatic summarization of data, extraction of the essence of information stored, and the discovery of patterns in raw data. … Related articles

Feature selection for effective text classification using semantic information R Jain, N Pise – International Journal of Computer …, 2015 – … Sleeping Experts algorithm [21], k-nearest neighbour classifier[17], Support Vector Machines [22][23] and neural networks [24][25 … Zhong, Wang Zhi-Fei, Jia Ke-Liang: Improving the Performance of Text Categorization using Automatic Summarization, International Conference … Cited by 1 Related articles All 6 versions

Multi technique amalgamation for enhanced information identification with content based image data R Das, S Thepade, S Ghosh – SpringerPlus, 2015 – Springer … Wavelet packets and Eigen values of Gabor filters were extracted as feature vectors by the authors in (Irtaza et al. 2013) for neural network architecture of image identification. … 4 Fusion technique for image identification. Artificial neural network (ANN) classifier. … Cited by 2 Related articles All 11 versions

Compact Feature Set Using Semantic Information For Text Classification RJN Pise – … Sleeping Experts algorithm [21], k-nearest neighbour classifier[17], Support Vector Machines [22][23] and neural networks [24][25 … Zhong, Wang Zhi-Fei, Jia Ke-Liang: “Improving the Performance of Text Categorization using Automatic Summarization”, International Conference … Related articles

Big data driven natural language processing research and applications V Gudivada, D Rao, V Raghavan – Big Data Analytics, 2015 – Page 222. Chapter 9 Big Data Driven Natural Language Processing Research and Applications Venkat N. Gudivada?, 1, Dhana Rao†, Vijay V. Raghavan‡ ? East Carolina University, Greenville, North Carolina, USA † Marshall … Cited by 7 Related articles

Multi-Document Summarization and Semantic Relatedness O Mogren – 2015 – … The objective of automatic summarization is to capture the most important topics in a set of documents, and to present them briefly … to the semantic similarity task, while (Tai, Socher, and Manning 2015) proposed a variant of the LSTM recurrent neural network architecture, where … Related articles All 3 versions

What Makes It Difficult to Understand a Scientific Literature? M Cao, J Tian, D Cheng, J Liu… – … , Knowledge and Grids ( …, 2015 – … For example, the state-of-the-art results on automatic summarization are not quiet readable yet [6]. Almost all question-answering systems … Recently, statistics machine learning methods such as topic models [20] and deep neural network (NN) models [16][17][18] have achieved … Related articles All 6 versions

Boosting Algorithm and Meta-Heuristic Based on Genetic Algorithms for Textual Plagiarism Detection HA Bouarara, RM Hamou, A Rahmani… – International Journal of …, 2015 – … procedures under- standable to the user, because decision trees graphically represent a set of rules and it is easily interpretable, it can process all types of data (quantitative and qualitative), fast classification compared to other algorithms (neural networks, SVM) and robust to … Cited by 4 Related articles All 2 versions

[BOOK] Improving the Performance of Text Summarization M Valizadeh – 2015 – … Abstract This thesis is concerned with the area of automatic summarization of multiple documents. … Some machine learning methods that are described here have been used further on in this thesis (eg neural networks and random forests) or by other researchers in their work on … Related articles All 2 versions

Swarm Semantic Hybrid Approach for Multi-document Abstractive Summarization A Khan, N Salim, AI Obasa – … across several documents [9]. Previous abstractive summarization approaches rely on human experts to construct domain ontology and rules; and then semantic representation of source document is built from them, which is a drawback of an automatic summarization system. … Related articles

Full Length Research Article S Kohli, N Mishra, DS Rajpoot – 2015 – … The strengths of this paper are use of multiple deep neural network model networks for performance enhancement and reduced … of the speech recognisation, it can be used in many mining applications like automatic indexing, automatic summarization, automatic classification. … Related articles All 2 versions

ExB Text Summarizer S Thomas, C Beutenmüller… – … Annual Meeting of …, 2015 – … This paper describes our automatic summarization system, and its partici- pation in the MultiLing 2015 summarization chal- lenge. … El-Haj and Rayson (2013), singu- lar value decomposition on a term-vector matrix (Steinberger, 2013) and neural network-derived transformations … Cited by 1 Related articles All 10 versions

Satellite images-based obstacle recognition and trajectory generation for agricultural vehicles M Bodur, M Mehrolhassani – International Journal of Advanced …, 2015 – … execution of paths in real-time. A complete coverage path-planning algorithm is proposed to generate dynamic paths, which avoid obstacles for a cleaning robot using neural networks [37]. A four-layer path-planning algorithm … Cited by 2 Related articles All 6 versions

A Modular System For Support Of Experiments In Text Classification Modularny System WSPOMAGANIA DO?WIADCZE? Z … M PTASZYNSKI, P LEMPA, F MASUI – … One of the disadvantages of using standard classification algorithms, such as SVM, or Neural Networks, and making them inapplicable in … In the near future we plan to perform automatic summarization of sentence templates to increase the readability and informativeness of the … Related articles All 4 versions

Figure-Associated Text Summarization and Evaluation BP Ramesh, RJ Sethi, H Yu – PloS one, 2015 – Biomedical literature incorporates millions of figures, which are a rich and important knowledge resource for biomedical researchers. Scientists need access to the figures and the knowledge they represent in order to validate research findings and to generate new hypotheses. By … Cited by 1 Related articles All 20 versions

The Statement of Originality M Yousefiazar – 2015 – … for computer vision, that shows promising results to produce a compelling automatic summarization system for documents. … are either positive or negative (ie a binary label). Recursive neural networks (RNNs) in which the same set of weights applies recursively have been … Related articles All 2 versions

Data Mining in Research Keypad of Discoverer B Biswas – proceedings of 3rd national conference on Research … – … These needs are automatic summarization of data, extraction of the “real meaning” of information stored, and the innovation of … given below:- a) Artificial neutral networks – Nonlinear predictive models that learn through trainingand resemble biological neural network in structure … Cited by 1 Related articles All 2 versions

End-Shape Analysis for Automatic Segmentation of Arabic Handwritten Texts AT Jamal – 2015 – … For example, words need to be extracted to improve text-to-speech methods. Automatic summarization, translation, natural language understanding, part-of-speech tagging, text-proofing, text simplification, and automated essay … Related articles All 2 versions

Topic Modeling for Speech and Language Processing JT Chien – Modern Methodology and Applications in Spatial- …, 2015 – Springer … language. LM is not only useful for speech recognition but also for many other information systems including optical character recognition, spell correction, question answering, automatic summarization, information retrieval, etc. … Related articles All 3 versions

Supervised Learning Approaches for Automatic Structuring of Videos C SCHMID – 2015 – Citeseer Page 1. THÈSE Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ GRENOBLE ALPES Spécialité : Mathématiques et Informatique Arrêté ministériel : 7 août 2006 Présentée par Danila POTAPOV Thèse dirigée par Cordelia SCHMID et codirigée par Zaid HARCHAOUI … Related articles All 2 versions

Development emails content analyzer: Intention mining in developer discussions (T) A Di Sorbo, S Panichella, CA Visaggio… – … (ASE), 2015 30th …, 2015 – Page 1. Development Emails Content Analyzer: Intention Mining in Developer Discussions Andrea Di Sorbo ? , Sebastiano Panichella † , Corrado A. Visaggio ? , Massimiliano Di Penta ? , Gerardo Canfora ? and Harald C. Gall † … Cited by 11 Related articles All 4 versions

Predicting associated statutes for legal problems YH Liu, YL Chen, WL Ho – Information Processing & Management, 2015 – Elsevier … documents. Chou and Hsing (2010) developed a legal document classification, clustering, and search methodology based on neural network technology, helping law enforcement to manage criminal written judgments. Chen … Cited by 3 Related articles All 3 versions

Summarizing a document by trimming the discourse tree T Hirao, M Nishino, Y Yoshida, J Suzuki… – IEEE/ACM Transactions …, 2015 – … problem. Denil et al. [16] proposed a method that can handle not only semantic similarity between sentences but also the order of sen- tences in a document by exploiting the power of artificial con- volutional neural networks. The … Related articles All 4 versions

Social Media Story Telling P Hennig, P Berger, C Dullweber… – Smart City/ …, 2015 – … Simultaneously the library allows the detection of sentiments by using machine learning with neural networks and a model trained on labeled sentences. … 379–387. [6] FCT Chua and S. Asur, “Automatic summarization of events from social media.” in ICWSM, 2013. … Related articles All 2 versions

Microblogging Temporal Summarization: Filtering Important Twitter Updates for Breaking News T Xu – 2015 – … to future research directions at the intersection of social media, computational jour- nalism, information retrieval, automatic summarization, and machine learning. Page 3. … 12 Page 25. media, computational journalism, information retrieval, automatic summarization, … Related articles

Mongolian Named Entity Recognition using suffixes segmentation W Wang, F Bao, G Gao – Asian Language Processing (IALP), …, 2015 – … An NER system can serve as a valuable component for many systems, such as Question Answering, Machine Translation, Social Media Analysis, Semantic Search or Automatic Summarization. Nowadays, many approaches have been proposed and in the published … Cited by 1 Related articles

Towards Large Scale Summarization JM Christensen – 2015 – … BACKGROUND Researchers have studied automatic summarization extensively, with earliest works dat- ing back half a century ago (Luhn, 1958). … models (Conroy and O’leary, 2001), log-linear models (Osborne, 2002), and neural networks (Svore et al., 2007). Svore et al. … Cited by 1 Related articles All 3 versions

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain H Moen, F Ginter, E Marsi… – BMC medical …, 2015 – bmcmedinformdecismak. … … Models include variants of random indexing and the semantic neural network model word2vec. … Secondly, when combined with systems for automatic summarization and trend detection, it could help health care managers to optimally allocate human resources with almost real … Cited by 4 Related articles All 14 versions

Reputation-Based Trust Evaluation By Extracting User’S Assessment N Sushma, GV Kondareddy – … The field combines tools from statistics and artificial intelligence such as neural networks and machine learning with database management to analyze large … The following is a list of some of the most commonly researched tasks in NLP: 1. Automatic summarization-Produce a … Related articles

Audiovisual framework for automatic soccer highlights generation A Raventós Mayoral – 2015 – … It firstly segments the whole video sequence into video shots, then it classifies the resulted shots into different shot-type classes. Afterwards, the system ap- plies a support vector machine and an artificial neural network algorithm for identifying Page 12. Introduction 3 … Related articles

Sentiment Classification of Arabic Documents: Experiments with multi-type features and ensemble algorithms. A Bayoudhi, H Ghorbel, LH Belguith – PACLIC, 2015 – Citeseer … 3.6 Learning Algorithm Apart from classification features, Sentiment classification task depends highly on the used learning algorithm. According to the literature, the most popular algorithms are NB, SVM, MaxEnt, Artificial Neural Networks (ANN). … Related articles All 10 versions

Feature engineering for MEDLINE citation categorization with MeSH AJJ Yepes, L Plaza… – BMC …, 2015 – bmcbioinformatics.biomedcentral. … … On the other hand, most previous work relies on comparing or combining several ML algorithms (Bayesian models, neural networks, decision trees, regression, etc … shown to be of use in different tasks [8,9], such as information retrieval [7,45,46] and automatic summarization [47]. … Cited by 5 Related articles All 19 versions

Tell me why: uma arquitetura para fornecer explicações ricas sobre revisões V Woloszyn – 2015 – … ANN Artificial Neural Network LSA Latent Semantic Analysis SVD Singular Value Decomposition … 17 Figure 2.2 Quotation location within document ….. 25 Figure 2.3 Three-layer Artificial Neural Network ….. … Related articles All 2 versions

Digital technologies and artificial intelligence’s present and foreseeable impact on lawyering, judging, policing and law enforcement E Nissan – AI & SOCIETY – Springer … Types of data mining include, for example, predictive data mining (whose aim is to learn from sample data in order to make a prediction and whose techniques include neural networks, rule induction, linear, multiple regression); segmentation (whose aim is to automatically … Related articles All 2 versions

Compact multiview representation of documents based on the total variability space M Morchid, M Bouallegue, R Dufour, G Linarès… – IEEE/ACM Transactions …, 2015 – Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 8, AUGUST 2015 1295 Compact Multiview Representation of Documents Based on the Total Variability Space Mohamed … Cited by 3 Related articles All 7 versions

Automatic Arabic text summarization: a survey Asma Bader Al-Saleh & Mohamed El B Menai – … In addition, although the field of automatic summarization is over 50 years old (Luhn 1958; Edmundson 1969), many problems still need solutions. For example, managing summary evaluation challenges is an open issue in text summarization (Saggion and Poibeau 2013). … Related articles

What, Where and How? Introducing pose manifolds for industrial object manipulation R Kouskouridas, A Amanatiadis… – Expert Systems with …, 2015 – Elsevier In this paper we propose a novel method for object grasping that aims to unify robot vision techniques for efficiently accomplishing the demanding task of auton. Cited by 1 Related articles All 5 versions

Automated Complaint System Using Text Mining Techniques MRA ALNajjar, ELH Alaa – … 41 4.8.1 Automatic summarization ….. 42 4.8.2 A popular Summarization methods that deal with Arabic text ….. 42 … ME Maximum Entropy NN Neural Networks DFE Discriminative Frequency Estimate Page 14. 3 Chapter 1 … Related articles

Automatically creating adaptive video summaries using constraint satisfaction programming: Application to sport content H Boukadida, SA Berrani, P Gros – IEEE Transactions on …, 2015 – … This evaluation involved more than 60 people. Experiments have been performed within the challenging application of tennis match automatic summarization, using about 28.5 hours of videos. Index Terms—Video analysis, video summarization, CSP. … Cited by 1 Related articles

Exploring Weights of Hierarchical and Equivalency Relationship in General Persian Texts A Shahriari, H Parvin, A Monajati – … Applications of Neural Networks ( …, 2015 – Page 1. Exploring Weights of Hierarchical and Equivalency Relationship in General Persian Texts Afshin Shahriari Islamic Azad University, Nourabad Mamasani Branch, Department of Computer Science Nourabad Mamasani … Related articles

[BOOK] Advances in Artificial Intelligence and Its Applications: 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Cuernavaca, Morelos, … OP Lagunas, OH Alcántara, GA Figueroa – 2015 – … The first volume, Advances in Artificial Intelligence and Soft Computing, contains 46 papers structured into eight sections: – Invited Paper – Natural Language Processing – Logic and Multi-agent Systems – Bioinspired Algorithms – Neural Networks – Evolutionary Algorithms … Related articles All 4 versions

Natural language processing for social media A Farzindar, D Inkpen – Synthesis Lectures on Human …, 2015 – Page 1. N atural Language P rocessing for S ocial Media – F arzindar and Inkpen Page 2. Page 3. Natural Language Processing for Social Media Page 4. Page 5. Synthesis Lectures on Human Language Technologies Editor Graeme Hirst, University of Toronto … Cited by 7 Related articles All 6 versions

Culture Clubs Processing Speech by Deriving and Exploiting Linguistic Subcultures DG Brizan – 2015 – Page 1. Culture Clubs Processing Speech by Deriving and Exploiting Linguistic Subcultures by David Guy Brizan Thesis Proposal for the degree of Doctor of Philosophy at the Graduate Center of the City University of New York … Related articles All 3 versions

Automated generation of movie tributes AMS Aparício – 2015 – … arg max s?Un i=1Si |{Si : s ? Si}| (3.3) 3.1.2 Diversity A very common problem in automatic summarization is the presence of redundant in- formation in the final summary. In order to solve this issue, the following algorithms were developed to guarantee diversity. … Related articles All 3 versions

Joint parsing of syntactic and semantic dependencies X Lluís – 2015 – … tems that use the output of dependency parsing and SRL analysis for several applications, including automatic summarization (Melli et al., 2006), question answering (Narayanan and Harabagiu, 2004), information extraction (Surdeanu … Related articles All 2 versions

Automatic reconstruction of itineraries from descriptive texts L Moncla – 2015 – Page 1. Automatic reconstruction of itineraries from descriptive texts Ludovic Moncla To cite this version: Ludovic Moncla. Automatic reconstruction of itineraries from descriptive texts. Information Retrieval [cs.IR]. Université de … Cited by 2 Related articles All 5 versions

A systematic review of scholar context-aware recommender systems ZD Champiri, SR Shahamiri, SSB Salim – Expert Systems with Applications, 2015 – Elsevier Incorporating contextual information in recommender systems is an effective approach to create more accurate and relevant recommendations. This review has been. Cited by 19 Related articles All 9 versions

Web Mining for the Integration of Data Mining with Business Intelligence in Web-Based Decision Support Systems MA Domingues, AM Jorge, C Soares… – Integration of Data …, 2015 – … namic recommendations (eg, pages, ser- vices, etc) for each web user (Anand, & Mobasher, 2003); • Categorization/Clustering of Content: Content data can be used to categorize/ cluster web pages into topic directories (Chakrabarti, 2000); • Automatic Summarization of Content … Related articles All 4 versions

State of the Art in Cross-Media Analysis, Metadata Publishing, Querying and Recommendations P Aichroth, J Björklund, F Stegmaier, T Kurz, G Miller – 2015 – Page 1. State of the Art in Cross-Media Analysis, Metadata Publishing, Querying and Recommendations Responsible editor(s): Patrick Aichroth, Johanna Björklund, Florian Stegmaier, Thomas Kurz, Grant Miller Volume 1 Page 2. … Related articles

A tree-based learning approach for document structure analysis and its application to web search FC Pembe, T Güngör – Natural Language Engineering, 2015 – Cambridge Univ Press … We also analyzed the effect of document structuring on automatic summarization in the context of Web search. … In this approach, we analyzed the effect of structural information in automatic summarization using English document collections and queries. … Related articles All 7 versions

Constructing Predictive Model using Data Mining Techniques in Support of Motor Insurance Policy Risk Assessment F Yihenew – 2015 – … this study and the result of k-means clustering, J48 decision tree algorithm and multilayerperceptron neural network. The last chapter provides conclusion and recommendation for future work. … better managerial choices. These needs are automatic summarization of data, … Related articles

Normalized compression distance of multisets with applications AR Cohen, PMB Vitányi – IEEE transactions on pattern analysis …, 2015 – Page 1. Normalized Compression Distance of Multisets with Applications Andrew R. Cohen and Paul MB Vit anyi Abstract—Pairwise normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity metric based on compression. … Cited by 8 Related articles All 25 versions

Modeling words for online sexual behavior surveillance and clinical text information extraction JA Fries – 2015 – … 24 2.3.5 Recurrent Neural Networks . . . . . … enabling complex information retrieval tasks that require some degree of logical inference. Automatic summarization (generating condensed representations of documents), question … Cited by 1 Related articles

On the Helmholtz principle for text mining B Dadachev – 2015 – … 75 6 Automatic Summarization 76 6.1 A brief literature review . . . . … This is why supervised learning ap- proaches are often preferred; a large number of algorithms are nowadays available, such as decision trees, linear classifiers and artificial neural networks [30]. Supervised … Related articles All 5 versions

Semantic-enriched visual vocabulary construction in a weakly supervised context MA Rizoiu, J Velcin, S Lallich – Intelligent Data Analysis, 2015 – … The Web 2.0 allowed easy image sharing and recently even search capabilities (eg, Instagram,1 Flickr2). Social Networks rely heavily on image sharing. Because of the sheer volumes of created images, automatic summarization, search and classification methods are required. … Cited by 2 Related articles All 9 versions

Profile-Based Summarisation for Web Site Navigation A Alhindi, U Kruschwitz, C Fox, M Albakour – ACM Transactions on …, 2015 – Page 1. 4 Profile-Based Summarisation for Web Site Navigation AZHAR ALHINDI, UDO KRUSCHWITZ, and CHRIS FOX, University of Essex M-DYAA ALBAKOUR, University of Glasgow Information systems that utilise contextual … Cited by 2 Related articles All 11 versions

Automatic reconstruction of itineraries from descriptive texts L Moncla, FJ Nogueras Iso, M Gaio – 2015 – Page 1. Page 2. Page 3. Page 4. Page 5. 1.2. Challenges Computer science also makes the connection between linguistics and geography thanks to NLP and GIS. The main goal of our work is to automatically extract and interpret … Related articles All 2 versions

Social Aspects of Business Informatics A Marciniak, M Morzy – Page 1. Social Aspects of Business Informatics Concepts and Applications Scientific Editors Andrzej Marciniak Miko?aj Morzy Page 2. Conferences organized by the Polish Information Processing Society: IX edition of the Congress of Young IT Scientists … Related articles

Flank Wear Characterization using Image Analysis C Johansson – Page 1. MASTER’S THESIS Flank Wear Characterization using Image Analysis Christer Johansson 2015 Master of Science in Engineering Technology Materials Engineering Luleå University of Technology Department of Engineering Sciences and Mathematics Page 2. … Related articles

Flank Wear Characterization using Image Analysis Christer Johansson 2015 Master of Science in Engineering Technology Materials Engineering Luleå University of Technology Department of Engineering Sciences and Mathematics Page 2. … Related articles