General Information
NameProf. Lior Rokach
DepartmentThe Faculty of Engineering Sciences
Emailliorrk@bgu.ac.il
Personal Web SitePersonal Web Site
Academic RankProfessor


Books

 
[1] Rokach L., A survey of data leakage detection and prevention solutions, Springer, (2012).
[2] Kantor, B ., Rokach L., Ricci, Francesco, Recommender systems handbook, Springer, (2011).
[3] Ricci, Rokach L., Francesco, Kantor, B ., Recommender systems handbook, Springer, (2011).
[4] Rokach L., Building effective recommender systems, Springer, (2009).
[5] Rokach L., Maimon Oded, Soft Computing for Knowledge Discovery and Data Mining, (2007).
[6] Rokach L., Maimon Oded, Data Mining with Decision Trees: Theory & Applications, World scientific, (2007).
[7] Maimon Oded, Rokach L., Decomposition Methodology for Knowledge Discovery and Data Mining: Theory and Applications, (2005).
[8] Maimon Oded, Rokach L., The Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, (2005).

Show All
   

To the top

Book in Series

 
[1] Romano R., Rokach L., Maimon O., Automatic discovery of regular expression patterns representing negated findings in medical narrative reports, Springer, 300-311, (2006).
[2] Rokach L., Maimon O., Averbuch M., Information retrieval system for medical narrative reports, Springer-Verlag Berlin, BERLIN, 217-228, (2004).
[3] Rokach L., Maimon O., Lavi I., Space decomposition in data mining: A clustering approach, Springer, 24-31, (2003).

Show All
   

To the top

Book Chapters

 
[1] Rokach L., Links Reconstruction Attack Using Link Prediction Algorithms to Compromise Social Networks Privacy, Springer, (2012).
[2] Levy Meira, Rokach L., Personalized Knowledge service Based on Smart Cell-phone Usage: A Conceptual Framework, Knowledge Service Engineering Handbook, CRC press, (2012).
[3] Rokach L., An overview of IDS Using Anomaly Detection, IGI Global, 327-337, (2007).
[4] Ricci F, Rokach L., Introduction to Recommender Systems, in Recommender Systems Handbook, Ricci, F. Rokach, L. and Shapira,B. (Eds). Springer (forthcoming), ().

Show All
   

To the top

Journal Articles

 
[1] Rokach L., Decision forest: Twenty years of research, Inf. Fusion (Netherlands), 27, 111 - 25, (2016).
[2] Rokach L., A Classifier to Determine Which Wikipedia Biographies Will Be Accepted, J. Assoc. Inf. Sci. Technol. (USA), 66, 1, 213 - 18, (2015).
[3] Rokach L., pcStream: A Stream Clustering Algorithm for Dynamically Detecting and Managing Temporal Contexts, Advances in Knowledge Discovery and Data Mining.19th Pacific-Asia Conference, PAKDD 2015. Proceedings: LNCS 9078, pt. II, 119 - 33, (2015).
[4] Rokach L., Fast and space-efficient shapelets-based time-series classification, Intell. Data Anal. (Netherlands), 19, 5, 953 - 81, (2015).
[5] Rokach L., Fast item-based collaborative filtering, 7th International Conference on Agents and Artificial Intelligence (ICAART 2015). Proceedings, vol.2, 457 - 63, (2015).
[6] Rokach L., Unknown malware detection using network traffic classification, 2015 IEEE Conference on Communications and Network Security (CNS), 134 - 42, (2015).
[7] Rokach L., Local-shapelets for fast classification of spectrographic measurements, Expert Syst. Appl. (Netherlands), 42, 6, 3150 - 8, (2015).
[8] Rokach L., Reaching a joint decision with minimal elicitation of voter preferences, Inf. Sci. (Netherlands), 278, 466 - 87, (2014).
[9] Rokach L., Optimizing Data Misuse Detection, ACM Trans. Knowl. Discov. Data (USA), 8, 3, 16 (23 pp.) -, (2014).
[10] Rokach L., Mobile malware detection through analysis of deviations in application network behavior, Computers and Security, 43, 1 - 18, (2014).
[11] Rokach L., Ensemble methods for multi-label classification, Expert Syst. Appl. (UK), 41, 16, 7507 - 23, (2014).
[12] Rokach L., Survival analysis of automobile components using mutually exclusive forests, IEEE Trans. Syst. Man Cybern. Syst. (USA), 44, 2, 246 - 53, (2014).
[13] Rokach L., Adapted Features and Instance Selection for Improving Co-training, Mach. Learn. (Netherlands), 91, 1, 81 - 100, (2014).
[14] Rokach L., Methodology for Connecting Nouns to Their Modifying Adjectives, Computational Linguistics and Intelligent Text Processing. 15th International Conference, CICLing 2014. Proceedings: LNCS 8403, pt. I, 271 - 84, (2014).
[15] Rokach L., ConfDTree: a statistical method for improving decision trees, J. Comput. Sci. Technol. (USA), 29, 3, 392 - 407, (2014).
[16] Rokach L., Neighborhood evaluation in recommender systems using the realization based entropy approach, Int. J. Bus. Anal. (Malaysia), 1, 4, 34 - 50, (2014).
[17] Rokach L., Novel active learning methods for enhanced PC malware detection in windows OS, Expert Syst. Appl. (UK), 41, 13, 5843 - 57, (2014).
[18] Freilikhman, Rokach L., Shirley, Facebook single and cross domain data for recommendation systems, , 23, 211--247, (2013).
[19] Albayrak, Rokach L., Sahin, Editorial: Guest editorial: Special issue on data mining for information security, , 231, 1--3, (2013).
[20] Dror M., Rokach L., Shabtai ., OCCT: A One-Class Clustering Tree for Implementing One-to-Many Data Linkage, , 1, (2013).
[21] Rokach L., A GIS-based decision support system for hotel room rate estimation and temporal price prediction: the hotel brokers' context, Decis. Support Syst. (Netherlands), 54, 2, 1119 - 33, (2013).
[22] Rokach L., IP2User - Identifying the Username of an IP Address in Network-related Events, 2013 IEEE International Congress on Big Data, 435 - 6, (2013).
[23] Rokach L., Improving Sentiment Analysis in an Online Cancer Survivor Community Using Dynamic Sentiment Lexicon, 2013 International Conference on Social Intelligence and Technology (SOCIETY), 109 - 13, (2013).
[24] Rokach L., Entity Matching in Online Social Networks, 2013 International Conference on Social Computing (SocialCom), 339 - 44, (2013).
[25] Rokach L., Ensemble of feature chains for anomaly detection, Multiple Classifier Systems. 11th International Workshop, MCS 2013. Proceedings, 295 - 306, (2013).
[26] Rokach L., A fast and scalable method for threat detection in large-scale DNS logs, 2013 IEEE International Conference on Big Data, 738 - 41, (2013).
[27] Rokach L., Detecting application update attack on mobile devices through network features, 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 91 - 2, (2013).
[28] Rokach L., Parsimonious citer-based measures: The artificial intelligence domain as a case study, J. Am. Soc. Inf. Sci. Technol. (USA), 64, 9, 1951 - 9, (2013).
[29] Bar, Rokach L., Ariel, Schclar, Alon, Boosting Simple Collaborative Filtering Models Using Ensemble Methods, , abs/1205.1357, 339-348, (2012).
[30] Antwarg, Rokach L., Liat, Attribute-Driven Hidden Markov Model Trees for Intention Prediction, , 42, 1103-1119, (2012).
[31] Antwarg, Liat, Rokach L., Lavie, Talia, Highlighting items as means of adaptive assistance, , 1--17, (2012).
[32] Chekina, Lena, Gutfreund, Rokach L., Dan, Kontorovich, Aryeh, Exploiting label dependencies for improved sample complexity, , 1--42, (2012).
[33] Shmueli, Erez, Tassa, Tamir, Rokach L., Wasserstein, Raz, Limiting disclosure of sensitive data in sequential releases of databases, , 191, 98--127, (2012).
[34] Rokach L., User identity verification via mouse dynamics, Inf. Sci. (USA), 201, 19-36, (2012).
[35] Harel, Amir, Rokach L., M-Score: A Misuseability Weight Measure, , 9, 414--428, (2012).
[36] Menahem, Eitan, Rokach L., Schclar, Alon, Securing Your Transactions: Detecting Anomalous Patterns In XML Documents, , abs/1209.1797, (2012).
[37] Rokach L., Detecting unknown computer worm activity via support vector machines and active learning, Pattern Anal. Appl. (UK), 15, 4, 459--475, (2012).
[38] Schclar, Rokach L., Alon, Abramson, Adi, User Authentication Based on Representative Users, , 42, 1669--1678, (2012).
[39] Tahan, Rokach L., Gil, Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features, , 98888, 949--979, (2012).
[40] Rokach L., Machine-learning-based circuit synthesis, 2012 IEEE 27th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2012), 5 pp. -, (2012).
[41] Menahem, Rokach L., Eitan, Combining One-Class Classifiers via Meta-Learning, , abs/1112.5246, (2011).
[42] Weiss, Yael, Rokach L., The CASH algorithm-cost-sensitive attribute selection using histograms, , (2011).
[43] Rokach L., Ensemble-Based Classifiers, AI Review, 33, 1-2, 1-39, (2010).
[44] Rokach L., Efficient Multi Dimensional Suppression for k-Anonymity, IEEE Transactions on Data and Knowledge Engineering, 22, 3, 334-347, (2010).
[45] Matatov Nissim, Rokach L., Maimon Oded, Privacy-Preserving Data Mining: A Feature Set Partitioning Approach, Information Sciences, 180, 14, 2696-2720, (2010).
[46] Glezer Chanan, Rokach L., Auto-Sign: An Automatic Signature Generator for High-Speed Malware Filtering Devices, Computer Virology, 6, 91-103, (2010).
[47] Kantor, B ., Rokach L., Ricci, Francesco, Recommender systems handbook, , 67, 02, (2010).
[48] Kisilevich, Rokach L., Slava, Efficient multidimensional suppression for k-anonymity, , 22, 334--347, (2010).
[49] Tenenboim-Chekina, Rokach L., Lena, Identification of label dependencies for multi-label classification, , 53--60, (2010).
[50] Rokach L., Evaluating Ensembles of Classifiers, 2010 IEEE 26th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2010), 153 - 84, (2010).
[51] Rokach L., Introduction to Ensemble Learning, 2012 IEEE 12th International Conference on Data Mining (ICDM 2012), 19 - 63, (2010).
[52] Rokach L., Introduction to Pattern Classification, Comput. Stat. Data Anal. (Netherlands), 53, 4, 1 - 18, (2010).
[53] Menahem Eitan, Rokach L., Improving Malware Detection by Applying Multi-Inducer Ensemble, Computational Statistics and Data Analysis, 53, 4, 1483-1494, (2009).
[54] Rokach L., Collective-agreement-based pruning of ensembles, Collective Agreement-based Pruning of Ensembles, 53, 4, 1015 - 1026, (2009).
[55] Rokach L., Naamani Lihi, Active Learning Using Pessimistic Expectation Estimators, Control and Cybernetics, 38, 1, 261-280, (2009).
[56] Rokach L., Troika – An Improved Stacking Schema for Classification Tasks, Information Sciences, 179, 24, 4097-4122, (2009).
[57] Rokach L., Improving malware detection by applying multi-inducer ensemble, Computational Statistics & Data Analysis (CSDA), 53, 1483-1494, (2009).
[58] Menahem, Rokach L., Eitan, Troika--An improved stacking schema for classification tasks, , 179, 4097--4122, (2009).
[59] Rokach L., An Evolutionary Algorithm for Constructing a Decision Forest: Combining the Classification of Disjoints Decision Trees, International Journal of Intelligent Systems, (2008).
[60] Rokach L., Romano Roni, Maimon Oded, Mining Manufacturing Databases to Discover the Effect of Operation Sequence on the Product Quality, Journal of Intelligent Manufacturing, (2008).
[61] Rokach L., Detection of unknown computer worms based on behavioral classification of the host, Computational Statistics and Data Analysis, 52, 9, 4544 - 4566, (2008).
[62] Rokach L., Genetic algorithm-based feature set partitioning for classification problems, Pattern Recognition, 41, 5, 1693 - 1717, (2008).
[63] Rokach L., Pessimistic Cost-sensitive Active Learning of Decision Trees, Pattern Analysis and Machine Intelligence, (2008).
[64] Rokach L., Rokach L., Shmilovici A., Pessimistic cost-sensitive active learning of decision trees for profit maximizing targeting campaigns, Data Mining and Knowledge Discovery, 17, 2, 283 - 316, (2008).
[65] Cohen Shahar, Rokach L., Maimon Oded, Decision-tree instance-space decomposition with grouped gain-ratio, Information Sciences, 177, 17, 3592-3612, (2007).
[66] Rokach L., Chizi Barak, Maimon Oded, A Methodology for Improving the Performance of Non-ranker Feature Selection Filters, International Journal of Pattern Recognition and Artificial Intelligence, 21, 5, 1-22, (2007).
[67] Shani G., Meisles A., Gleyzer Y., Rokach L., Ben-Shimon D., A stereotypes-based hybrid recommender system for media items, AAAI Workshop - Technical Report, WS-07-08, 76 - 83, (2007).
[68] Rokach L., Maimon O., Arbel R., Selective voting - Getting more for less in sensor fusion, International Journal of Pattern Recognition and Artificial Intelligence, 20, 3, 329-350, (2006).
[69] Rokach L., Maimon O., Data mining for improving the quality of manufacturing: A feature set decomposition approach, Journal of Intelligent Manufacturing, 17, 3, 285-299, (2006).
[70] Rokach L., Decomposition Methodology for Classification Tasks – A Meta Decomposer Framework, Pattern Analysis & Applications, (2006).
[71] Rokach L., Arbel R., Classifier Evaluation Under Limited Resources, Pattern Recognition Letters, 27, 14, 1619 - 31, (2006).
[72] Rokach L., Mining Manufacturing Data Using Genetic Algorithms-Based Feature Set Decomposition, ijista, (2006).
[73] Rokach L., Decomposition methodology for classification tasks: a meta decomposer framework, Pattern Analysis and Applications, 9, 2-3, 257-271, (2006).
[74] Maimon O.., Rokach L., Top-down induction of decision trees classifiers - A survey, Ieee Transactions on Systems Man and Cybernetics Part C-applications and Reviews, 35, 4, 476-487, (2005).
[75] Averbuch M., Maimon O., Rokach L., Ezer E., Free-text information retrieval system for a rapid enrollment of patients into clinical trials. Clinical Pharmacology & Therapeutics, 77, 2, P13-P13, (2005).
[76] Rokach L., Maimon O., Feature Set Decomposition for Decision Trees, Journal of Intelligent Data Analysis, 9, 2, 131-158, (2005).
[77] Rokach L., Maimon O., Arad O., Improving Supervised Learning by Sample Decomposition, International Journal on Computational Intelligence and Applications, 5, 1, 37-54, (2005).
[78] Rokach L., Maimon O, Ensemble of Decision Trees for Mining Manufacturing Data Sets, Machine Engineering, 4, 1-2, (2004).
[79] Auerbuch M., Karson ., Ben-Ami ., Maimon ., Rokach L., Context-sensitive medical information retrieval. Medinfo. MEDINFO, 11, Pt 1, 6, (2004).
[80] Zeira, Gil, Maimon, Rokach L., Oded, Change detection in classification models induced from time series data, , 57, 101--125, (2004).
[81] Zeira, G, Maimon, Rokach L., O, Chapter 5 Change Detection in Classification Models Induced from Time Series Data, , 57, 99--122, (2004).
[82] Ossmy, Ori, Tam, Rokach L., Ofir, Inbar, Ohad, MINDDESKTOP: COMPUTER ACCESSIBILITY FOR SEVERELY HANDICAPPED, , (0).

Show All
   

To the top

Conference Proceedings

 
[1] Rokach L., Deep Auto-Encoding for Context-Aware Inference of Preferred Items’ Categories, RecSys16, ACM, (2016).
[2] Bar Ariel, Rokach L., Moshe Unger, Lior Rokach, Ariel Bar, Ehud Gudes, Bracha Shapira: Contexto: lessons learned from mobile context inference. UbiComp Adjunct 2014: 175-178, Ubicomp, (2014).
[3] Tenenboim Lena, Rokach L., Intruder or Welcome Friend: Inferring Group Membership in Online Social Networks, SBP, Springer, (2013).
[4] Rokach L., Chapnik, Eyal, Siboni, Gali, Recommending Insurance Riders, 247-268, (2013).
[5] Rokach L., Introducing diversity among the models of multi-label classification ensemble, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, (2012).
[6] Moreno Orly, Rokach L., TALMUD – Transfer Learning for Multiple Domains, ACM, (2012).
[7] Fire, Michael, Kagan, Rokach L., Dima, Data mining opportunities in geosocial networks for improving road safety, IEEE, 1--4, (2012).
[8] Katz, Gilad, Rokach L., Using Wikipedia to Boost SVD Recommender Systems, 19-36, (2012).
[9] Moreno, Orly, Rokach L., TALMUD: transfer learning for multiple domains, 425--434, (2012).
[10] Chekina, L, Rokach L., Mimran, D, Detection of Deviations in Mobile Applications Network Behavior, (2012).
[11] Rokach L., Meta-Learning for Selecting a Multi-Label Classification Algorithm, ICDM Workshop on Optimization based Techniques for Emerging Data Mining Problems, (2011).
[12] Fire Micky, Rokach L., Link Prediction in Social Networks using Computationally Efficient Topological Features, IEEE International Conference on Social Computing, (2011).
[13] Rami Puzis, Rokach L., Link Prediction in Social Networks using Computationally Efficient Topological Features, (2011).
[14] Rokach L., Using Wikipedia to boost collaborative filtering techniques, Recsys 2011, (2011).
[15] Dayan Aviram, Aydin Aykan, Rokach L., Biasdi Naseem, Katz Guy, Schwaiger Roland, Fishel Ramilda, Recommenders Benchmark Framework, Recommenders Benchmark Framework, ACM RecSys, (2011).
[16] Fire, Michael, Tenenboim, Lena, Rokach L., Lesser, Ofrit, Link prediction in social networks using computationally efficient topological features, IEEE Computer Society, 73--80, (2011).
[17] Bercovitch, M, Renford, M, Rokach L., Hasson, L, HoneyGen: An automated honeytokens generator, IEEE, 131--136, (2011).
[18] Gafny, Ma'ayan, Rokach L., Poster: applying unsupervised context-based analysis for detecting unauthorized data disclosure, 765--768, (2011).
[19] Harel, Amir, Rokach L., Dynamic Sensitivity-Based Access Control, IEEE, 201--203, (2011).
[20] Harel, Amir, Rokach L., Eliciting domain expert misuseability conceptions, 193--194, (2011).
[21] Keim Daniel, Rokach L., Geo-Spade: A Generic Google-Earth Based Framework For Analysis And Exploration Of Spatiotemporal Data, The 12th International Conference on Enterprise Information Systems (ICEIS 2010), (2010).
[22] Porat Talya, Naamani Lihi, Rokach L., Interactive Audience selection tool for distributing a mobile campaign, IADIS International Conference - Information Systems 2010, (2010).
[23] Gershman Amir, Meisels Amnon, Rokach L., A Decision Tree Based Recommender System, the 10th International conference on innovative Internet Community Systems, (2010).
[24] Keim Daniel, Rokach L., A novel approach to mining travel sequences using collections of geo-tagged photos, AGILE 2010, Springer, (2010).
[25] Porat Talya, Rokach L., Interactive Audience Selection Tool for Distributing a Mobile Campaign, IADIS International Conferencer, (2010).
[26] Rokach L., Iterative voting under uncertainty for group recommender systems, Proceedings of the Fourth ACM Conference on Recommender Systems, (2010).
[27] Rokach L., Identification of Label Dependencies for Multi-label Classification, ICML Workshop on Learning from Multi-Label Data (MLD’10), (2010).
[28] Dery L, Rokach L., Cost sensitive active learning algorithm for multiple parallel campaigns, IEEE 26th Convention of Electrical and Electronics Engineers in Israel, (2010).
[29] Marom, Rokach L., David ., Using the confusion matrix for improving ensemble classifiers, IEEE, 000555--000559, (2010).
[30] Gafny, Ma'ayan, Rokach L., Detecting data misuse by applying context-based data linkage, 3--12, (2010).
[31] Harel, Amir, Rokach L., M-score: estimating the potential damage of data leakage incident by assigning misuseability weight, 13--20, (2010).
[32] Rokach L., Clustering di-graphs for continuously verifying users according to their typing patterns,2010 IEEE 26th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2010), IEEE, 000445--000449, (2010).
[33] Rokach L., Continuous verification using keystroke dynamics,Proceedings 2010 International Conference on Computational Intelligence and Security (CIS 2010), IEEE Computer Society, 411--415, (2010).
[34] Rokach L., Schclar Alon, Random Projection Ensemble Classifiers, Lecture Notes in Business Information Processing, ICEIS, Springer, (2009).
[35] Rokach L., Multi-label Classification by Analyzing Labels Dependencies, ECML/PKDD Workshop on Learning from Multi-Label Data, (2009).
[36] Itach Ehud, Rokach L., An Ensemble Method for Multilabel Classification using Transportation model, ECML/PKDD Workshop on Learning from Multi-Label Data, (2009).
[37] Rokach L., A Methodology for the Design of a Fuzzy Data Warehouse, IS 2008, IEEE, (2008).
[38] Rokach L., Anytime AHP Method for Preferences Elicitation in Stereotype-Based Recommender System, ICEIS, (2008).
[39] Rokach L., kACTUS 2.0: Privacy Preserving in Classification Tasks using k-Anonymity, ISIPS 2008: Interdisciplinary Studies in Information Privacy and Security, New Brunswick, New Jersey, May 12, 2008, (2008).
[40] Naamani L., Rokach L., Shmilovici A., A logistic regression method for cost sensetive active learning, IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings, 707 - 710, (2008).
[41] Rokach L., A logistic regression method for cost sensetive active learning, IEEE 25th Convention of Electrical and Electronics Engineers in Israel (IEEEI 2008), IEEE, (2008).
[42] Meisels, Rokach L., Amnon, Piratla, Nischal, An interactive hybrid recommender system, (2008).
[43] Rokach L., Shani G., Rokach L., Meisles A., Piratla N., Ben-Shimon D., Establishing User Profiles in the MediaScout Recommender System, IEEE Symposium on Computational Intelligence and Data Mining,Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007, IEEE, 470 - 476, (2007).
[44] Zakin Ori, Levi M., Shafrir N., Rokach L., Sinter G., Pen O., Identifying Computers Hidden Behind a NAT using Machine Learning Techniques, ECIW 2007. The 6th European Conference on Information Warfare and Security, Defence College of Management and Technology, Shrivenham, UK, July 2-3, 2007, (2007).
[45] Rokach L., Recommender System from Personal Social Networks, Atlantic Web Intelligence Conference, 47-55, (2007).
[46] Rokach L., Naamani Lihi, Active Learning Using Conditional Expectation Estimators, ADMKD, (2007).
[47] Rokach L., Active Learning Using Conditional Expectation Estimators, ADMKD’2007, Systems Research Institute Polish Academy of Sciences, (2007).
[48] Ben-Shimon Dudu, Tsikinovsky Alex, Rokach L., Meisles Amnon, Shani Guy, Recommender System from Personal Social Networks, 5th Atlantic Web Intelligence Conference, (2007).
[49] Rokach L., Recommender System from Personal Social Networks, AWIC - 5th Atlantic Web Intelligence Conference 2007, Springer, (2007).
[50] Rokach L., Establishing User Profiles in the MediaScout Recommender System, cidm - Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, IEEE, (2007).
[51] Rokach L., A Stereotypes-Based Hybrid Recommender System for Media Items, AAAI Workshop on Recommender Systems, (2007).
[52] Meisles, Amnon, Gleyzer, Rokach L., Yan, Ben-Shimon, David, A stereotypes-based hybrid recommender system for media items, (2007).
[53] Rokach L., Mainon O., Decomposition methodology for classification tasks, 2005 IEEE International Conference on Granular Computing (IEEE Cat. No. 05EX1036),2005 IEEE International Conference on Granular Computing (IEEE Cat. No. 05EX1036), IEEE, 636 - 41, (2005).
[54] Maimon O., Rokach L., Improving supervised learning by feature decomposition, Foundations of Information and Knowledge Systems. Second International Symposium, FoIKS 2002. Proceedings (Lecture Notes in Computer Science Vol.2284),Foundations of Information and Knowledge Systems. Second International Symposium, FoIKS 2002. Proceedings (Lecture Notes in Computer Science Vol.2284), Springer, 178 - 96, (2002).
[55] Maimon O., Rokach L., Lavi I., Space decomposition in data mining - a clustering approach, 22nd Convention of Electrical and Electronics Engineers in Israel. Proceedings (Cat. No.02EX637),22nd Convention of Electrical and Electronics Engineers in Israel. Proceedings (Cat. No.02EX637), 101 - 4, (2002).
[56] Maimon O., Rokach L., Cohen S., Comparing classification models using expert knowledge, 6th World Multiconference on Systemics, Cybernetics and Informatics. Proceedings,6th World Multiconference on Systemics, Cybernetics and Informatics. Proceedings, 473 - 8, (2002).
[57] Rokach L., Mainon O., Theory and applications of attribute decomposition, Proceedings 2001 IEEE International Conference on Data Mining,Proceedings 2001 IEEE International Conference on Data Mining, IEEE Comput. Soc, 473 - 80, (2001).
[58] Baltrunas L, Kaminskas M, Ricci F, Luke K.H., Rokach L., Best Usage Context Prediction for Music Tracks, ACM recsys September 2010, Cars Workshop, ().

Show All
   

To the top

Technical Report

 
[1] Puzis Rami, Rokach L., (23417/2012), Computationally Efficient Link Prediction in Variety of Social Networks, (2012).
[2] Rokach L., (23419/2012), Predicting Student Exam''s Scores by Analyzing Social Network Data, (2012).

Show All
   

To the top

misc

 
[1] Bitton, Yehonatan, Fire, Michael, Rokach L., Kagan, Dima, Bar-Ilan, Judit, Social Network Based Search for Experts, (2012).
[2] Feher, Clint, Rokach L., Moskovitch, Rober, System for verifying user identity via mouse dynamics, (2012).
[3] Menahem, Rokach L., Eitan, Stacking schema for classification tasks, (2012).
[4] Shimshon, Tomer, Rokach L., Moskovitch, Robert, Method for continuously verifying user identity via keystroke dynamics, (2012).
[5] Meisels, Rokach L., Amnon, Piratla, Nischal, Interactive hybrid recommender system, (2011).
[6] Schclar, Rokach L., Alon, Glass, Gregor, Jepsen, Kathrin, Henke, Katja, System and method for the detection of usability problems in an interactive application, (2011).
[7] Mimran, David, Peretz, Rokach L., Shoval, Glass, Gregor, Henke, Katja, Schneider, Lutz, A system for detecting usability problems of users while using their mobile devices, (2011).
[8] Rokach L., Antwarg, Liat, Next-step prediction system and method, (2010).
[9] Menahem, Rokach L., Eitan, An improved stacking schema for classification tasks, (2009).

Show All
   

To the top

incollection

 
[1] Fire, Michael, Rokach L., Katz, Gilad, Links Reconstruction Attack, Springer, (2013).
[2] Fire, Michael, Katz, Gilad, Rokach L., Predicting student exam’s scores by analyzing social network data, Springer, (2012).
[3] Rokach L., Data Leakage/Misuse Scenarios, Springer, (2012).
[4] Rokach L., Future Trends in Data Leakage, Springer, (2012).
[5] Rokach L., Introduction to Information Security, Springer, (2012).
[6] Rokach L., Privacy, Data Anonymization, and Secure Data Publishing, Springer, (2012).
[7] Rokach L., A Taxonomy of Data Leakage Prevention Solutions, Springer, (2012).
[8] Weiss, Yael, Fledel, Rokach L., Yuval, Cost-Sensitive Detection of Malicious Applications in Mobile Devices, Springer, (2012).
[9] Ricci, Rokach L., Francesco, Introduction to recommender systems handbook, Springer, (2011).
[10] Kisilevich, Slava, Rokach L., kACTUS 2: Privacy preserving in classification tasks using k-Anonymity, Springer, (2009).

Show All