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2020 – today
- 2023
[j62]Seffi Cohen
, Niv Goldshlager, Bracha Shapira, Lior Rokach:
TTANAD: Test-Time Augmentation for Network Anomaly Detection. Entropy 25(5): 820 (2023)- [j61]Liat Antwarg, Chen Galed, Nathaniel Shimoni, Lior Rokach, Bracha Shapira:
Shapley-based feature augmentation. Inf. Fusion 96: 92-102 (2023) - [j60]Seffi Cohen, Niv Goldshlager, Lior Rokach, Bracha Shapira:
Boosting anomaly detection using unsupervised diverse test-time augmentation. Inf. Sci. 626: 821-836 (2023) - [c80]Tamar Didi, Ido Guy, Amit Livne, Arnon Dagan, Lior Rokach, Bracha Shapira:
Promoting Tail Item Recommendations in E-Commerce. UMAP 2023: 194-203 - [i32]Bar Vered, Guy Shtar, Lior Rokach, Bracha Shapira:
AMFPMC - An improved method of detecting multiple types of drug-drug interactions using only known drug-drug interactions. CoRR abs/2302.03355 (2023) - 2022
- [j59]Guy Shtar, Lior Rokach, Bracha Shapira, Elkana Kohn, Matitiahu Berkovitch, Maya Berlin:
Explainable multimodal machine learning model for classifying pregnancy drug safety. Bioinform. 38(4): 1102-1109 (2022) - [j58]Guy Shtar, Asnat Greenstein-Messica, Eyal Mazuz, Lior Rokach, Bracha Shapira:
Predicting drug characteristics using biomedical text embedding. BMC Bioinform. 23(1): 526 (2022) - [j57]Adir Solomon, Bracha Shapira, Lior Rokach:
Predicting application usage based on latent contextual information. Comput. Commun. 192: 197-209 (2022) - [j56]Amit Livne, Eliad Shem Tov, Adir Solomon, Achiya Elyasaf, Bracha Shapira, Lior Rokach:
Evolving context-aware recommender systems with users in mind. Expert Syst. Appl. 189: 116042 (2022) - [j55]Amir Olswang, Tom Gonda, Rami Puzis, Guy Shani, Bracha Shapira, Noam Tractinsky:
Prioritizing vulnerability patches in large networks. Expert Syst. Appl. 193: 116467 (2022) - [j54]Adir Solomon, Mor Kertis, Bracha Shapira, Lior Rokach:
A deep learning framework for predicting burglaries based on multiple contextual factors. Expert Syst. Appl. 199: 117042 (2022) - [j53]Adir Solomon, Michael Michaelshvili, Ron Bitton, Bracha Shapira, Lior Rokach, Rami Puzis, Asaf Shabtai:
Contextual security awareness: A context-based approach for assessing the security awareness of users. Knowl. Based Syst. 246: 108709 (2022) - [c79]Chen Yanai, Adir Solomon, Gilad Katz, Bracha Shapira, Lior Rokach:
Q-Ball: Modeling Basketball Games Using Deep Reinforcement Learning. AAAI 2022: 8806-8813 - [c78]Yarden Rotem, Nathaniel Shimoni, Lior Rokach, Bracha Shapira:
Transfer Learning for Time Series Classification Using Synthetic Data Generation. CSCML 2022: 232-246 - [c77]Tzoof Avny Brosh, Amit Livne, Oren Sar Shalom, Bracha Shapira, Mark Last:
BRUCE: Bundle Recommendation Using Contextualized item Embeddings. RecSys 2022: 237-245 - [c76]Sagi Eden, Amit Livne, Oren Sar Shalom, Bracha Shapira, Dietmar Jannach:
Investigating the Value of Subtitles for Improved Movie Recommendations. UMAP 2022: 99-109 - [e8]Jennifer Golbeck, F. Maxwell Harper, Vanessa Murdock, Michael D. Ekstrand, Bracha Shapira, Justin Basilico, Keld T. Lundgaard, Even Oldridge:
RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18 - 23, 2022. ACM 2022, ISBN 978-1-4503-9278-5 [contents] - [e7]Francesco Ricci, Lior Rokach, Bracha Shapira:
Recommender Systems Handbook. Springer US 2022, ISBN 978-1-0716-2196-7 [contents] - [r2]Francesco Ricci, Lior Rokach, Bracha Shapira:
Recommender Systems: Techniques, Applications, and Challenges. Recommender Systems Handbook 2022: 1-35 - [i31]Yarden Rotem, Nathaniel Shimoni, Lior Rokach, Bracha Shapira:
Transfer learning for time series classification using synthetic data generation. CoRR abs/2207.07897 (2022) - 2021
- [j52]Liat Antwarg, Ronnie Mindlin Miller, Bracha Shapira, Lior Rokach:
Explaining anomalies detected by autoencoders using Shapley Additive Explanations. Expert Syst. Appl. 186: 115736 (2021) - [j51]Itay Gabbay, Bracha Shapira, Lior Rokach:
Isolation forests and landmarking-based representations for clustering algorithm recommendation using meta-learning. Inf. Sci. 574: 473-489 (2021) - [j50]Adir Solomon, Amit Livne, Gilad Katz, Bracha Shapira, Lior Rokach:
Analyzing movement predictability using human attributes and behavioral patterns. Comput. Environ. Urban Syst. 87: 101596 (2021) - [c75]Amit Livne, Roy Dor, Bracha Shapira, Lior Rokach:
BNN: Boosting Neural Network Framework Utilizing Limited Amount of Data. CIKM 2021: 1150-1159 - [c74]Sagy Tuval, Bracha Shapira:
The next best question: a lazy, anytime framework for adaptive feature acquisition. SAC 2021: 1078-1081 - [i30]Seffi Cohen, Niv Goldshlager, Lior Rokach, Bracha Shapira:
Boosting Anomaly Detection Using Unsupervised Diverse Test-Time Augmentation. CoRR abs/2110.15700 (2021) - 2020
- [c73]Adir Solomon, Amit Magen, Simo Hanouna, Mor Kertis, Bracha Shapira, Lior Rokach:
Crime Linkage Based on Textual Hebrew Police Reports Utilizing Behavioral Patterns. CIKM 2020: 2749-2756 - [c72]Hagit Grushka-Cohen, Ofer Biller, Oded Sofer, Lior Rokach, Bracha Shapira:
Using Bandits for Effective Database Activity Monitoring. PAKDD (2) 2020: 701-713 - [c71]Dorin Shmaryahu, Guy Shani, Bracha Shapira:
Post-hoc Explanations for Complex Model Recommendations using Simple Methods. IntRS@RecSys 2020: 26-36 - [c70]Hen Tzaban, Ido Guy, Asnat Greenstein-Messica, Arnon Dagan, Lior Rokach, Bracha Shapira:
Product Bundle Identification using Semi-Supervised Learning. SIGIR 2020: 791-800 - [i29]Sigal Shaked, Amos Zamir, Roman Vainshtein, Moshe Unger, Lior Rokach, Rami Puzis, Bracha Shapira:
Sequence Preserving Network Traffic Generation. CoRR abs/2002.09832 (2020) - [i28]Asnat Greenstein-Messica, Roman Vainshtein, Gilad Katz, Bracha Shapira, Lior Rokach:
Automatic Machine Learning Derived from Scholarly Big Data. CoRR abs/2003.03470 (2020) - [i27]Amit Livne, Roy Dor, Eyal Mazuz, Tamar Didi, Bracha Shapira, Lior Rokach:
Iterative Boosting Deep Neural Networks for Predicting Click-Through Rate. CoRR abs/2007.13087 (2020) - [i26]Hagit Grushka-Cohen, Raphael Cohen, Bracha Shapira, Jacob Moran-Gilad, Lior Rokach:
A framework for optimizing COVID-19 testing policy using a Multi Armed Bandit approach. CoRR abs/2007.14805 (2020) - [i25]Amit Livne, Eliad Shem Tov, Adir Solomon, Achiya Elyasaf, Bracha Shapira, Lior Rokach:
Evolving Context-Aware Recommender Systems With Users in Mind. CoRR abs/2007.15409 (2020)
2010 – 2019
- 2019
- [j49]Victor Makarenkov, Lior Rokach, Bracha Shapira:
Choosing the right word: Using bidirectional LSTM tagger for writing support systems. Eng. Appl. Artif. Intell. 84: 1-10 (2019) - [j48]Avi Segal, Kobi Gal, Guy Shani, Bracha Shapira:
A difficulty ranking approach to personalization in E-learning. Int. J. Hum. Comput. Stud. 130: 261-272 (2019) - [j47]Victor Makarenkov, Ido Guy, Niva Hazon, Tamar Meisels, Bracha Shapira, Lior Rokach:
Implicit dimension identification in user-generated text with LSTM networks. Inf. Process. Manag. 56(5): 1880-1893 (2019) - [j46]Guy Shtar, Bracha Shapira, Lior Rokach:
Clustering Wi-Fi fingerprints for indoor-outdoor detection. Wirel. Networks 25(3): 1341-1359 (2019) - [c69]Noy Cohen-Shapira, Lior Rokach, Bracha Shapira, Gilad Katz, Roman Vainshtein:
AutoGRD: Model Recommendation Through Graphical Dataset Representation. CIKM 2019: 821-830 - [c68]Lior Perry, Bracha Shapira, Rami Puzis:
NO-DOUBT: Attack Attribution Based On Threat Intelligence Reports. ISI 2019: 80-85 - [c67]Shir Frumerman, Guy Shani, Bracha Shapira, Oren Sar Shalom:
Are All Rejected Recommendations Equally Bad?: Towards Analysing Rejected Recommendations. UMAP 2019: 157-165 - [i24]Victor Makarenkov, Lior Rokach, Bracha Shapira:
Choosing the Right Word: Using Bidirectional LSTM Tagger for Writing Support Systems. CoRR abs/1901.02490 (2019) - [i23]Victor Makarenkov, Ido Guy, Niva Hazon, Tamar Meisels, Bracha Shapira, Lior Rokach:
Implicit Dimension Identification in User-Generated Text with LSTM Networks. CoRR abs/1901.09219 (2019) - [i22]Liat Antwarg, Bracha Shapira, Lior Rokach:
Explaining Anomalies Detected by Autoencoders Using SHAP. CoRR abs/1903.02407 (2019) - [i21]Rami Puzis, Hadar Polad, Bracha Shapira:
Attack Graph Obfuscation. CoRR abs/1903.02601 (2019) - [i20]Guy Shtar, Lior Rokach, Bracha Shapira:
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures. CoRR abs/1903.04571 (2019) - [i19]Saar Tal, Bracha Shapira, Lior Rokach:
Personal Dynamic Cost-Aware Sensing for Latent Context Detection. CoRR abs/1903.05376 (2019) - [i18]Eran Fainman, Bracha Shapira, Lior Rokach, Yisroel Mirsky:
Online Budgeted Learning for Classifier Induction. CoRR abs/1903.05382 (2019) - [i17]Michael Shekasta, Gilad Katz, Asnat Greenstein-Messica, Lior Rokach, Bracha Shapira:
New Item Consumption Prediction Using Deep Learning. CoRR abs/1905.01686 (2019) - [i16]Avi Segal, Kobi Gal, Guy Shani, Bracha Shapira:
A difficulty ranking approach to personalization in E-learning. CoRR abs/1907.12047 (2019) - [i15]Guy Shtar, Bracha Shapira, Lior Rokach:
Clustering Wi-Fi Fingerprints for Indoor-Outdoor Detection. CoRR abs/1908.00758 (2019) - [i14]Roman Vainshtein, Gilad Katz, Bracha Shapira, Lior Rokach:
Assessing the Quality of Scientific Papers. CoRR abs/1908.04200 (2019) - [i13]Amit Livne, Moshe Unger, Bracha Shapira, Lior Rokach:
Deep Context-Aware Recommender System Utilizing Sequential Latent Context. CoRR abs/1909.03999 (2019) - [i12]Hagit Grushka-Cohen, Ofer Biller, Oded Sofer, Lior Rokach, Bracha Shapira:
Diversifying Database Activity Monitoring with Bandits. CoRR abs/1910.10777 (2019) - 2018
- [j45]Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel:
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442). Dagstuhl Manifestos 7(1): 96-139 (2018) - [j44]Moshe Unger, Bracha Shapira, Lior Rokach, Amit Livne:
Inferring contextual preferences using deep encoder-decoder learners. New Rev. Hypermedia Multim. 24(3): 262-290 (2018) - [j43]Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel:
The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction. SIGIR Forum 52(1): 91-101 (2018) - [c66]Noa Roy-Hubara, Lior Rokach, Bracha Shapira, Peretz Shoval:
Evaluation of a Design Method for Graph Database. BPMDS/EMMSAD@CAiSE 2018: 291-303 - [c65]Roman Vainshtein, Asnat Greenstein-Messica, Gilad Katz, Bracha Shapira, Lior Rokach:
A Hybrid Approach for Automatic Model Recommendation. CIKM 2018: 1623-1626 - [c64]Hagit Grushka-Cohen, Ofer Biller, Oded Sofer, Lior Rokach, Bracha Shapira:
Simulating User Activity for Assessing Effect of Sampling on DB Activity Monitoring Anomaly Detection. PADG@ESORICS 2018: 82-90 - [c63]Tom Gonda, Tal Pascal, Rami Puzis, Guy Shani, Bracha Shapira:
Analysis of Attack Graph Representations for Ranking Vulnerability Fixes. GCAI 2018: 215-228 - [c62]Liron Ben Kimon, Yisroel Mirsky, Lior Rokach, Bracha Shapira:
Utilizing Sequences of Touch Gestures for User Verification on Mobile Devices. PAKDD (3) 2018: 816-828 - [c61]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman:
DLRS 2018: third workshop on deep learning for recommender systems. RecSys 2018: 512-513 - [c60]Ido Guy, Bracha Shapira:
From Royals to Vegans: Characterizing Question Trolling on a Community Question Answering Website. SIGIR 2018: 835-844 - [c59]Adir Solomon, Ariel Bar, Chen Yanai, Bracha Shapira, Lior Rokach:
Predict Demographic Information Using Word2vec on Spatial Trajectories. UMAP 2018: 331-339 - [c58]Ido Guy, Victor Makarenkov, Niva Hazon, Lior Rokach, Bracha Shapira:
Identifying Informational vs. Conversational Questions on Community Question Answering Archives. WSDM 2018: 216-224 - [p3]Peter Brusilovsky, Barry Smyth, Bracha Shapira:
Social Search. Social Information Access 2018: 213-276 - [e6]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman:
Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2018, Vancouver, BC, Canada, October 6, 2018. ACM 2018, ISBN 978-1-4503-6617-5 [contents] - [i11]Shahar Admati, Lior Rokach, Bracha Shapira:
Wikibook-Bot - Automatic Generation of a Wikipedia Book. CoRR abs/1812.10937 (2018) - 2017
- [j42]Noa Roy-Hubara, Lior Rokach, Bracha Shapira, Peretz Shoval:
Modeling Graph Database Schema. IT Prof. 19(6): 34-43 (2017) - [j41]Yisroel Mirsky, Asaf Shabtai, Bracha Shapira, Yuval Elovici, Lior Rokach:
Anomaly detection for smartphone data streams. Pervasive Mob. Comput. 35: 83-107 (2017) - [c57]Tom Gonda, Rami Puzis, Bracha Shapira:
Scalable Attack Path Finding for Increased Security. CSCML 2017: 234-249 - [c56]Hadar Polad, Rami Puzis, Bracha Shapira:
Attack Graph Obfuscation. CSCML 2017: 269-287 - [c55]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk:
DLRS 2017: Second Workshop on Deep Learning for Recommender Systems. RecSys 2017: 370-371 - [c54]Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar:
Inferring Contextual Preferences Using Deep Auto-Encoding. UMAP 2017: 221-229 - [c53]Liron Ben Kimon, Yisroel Mirsky, Lior Rokach, Bracha Shapira:
User Verification on Mobile Devices Using Sequences of Touch Gestures. UMAP 2017: 365-366 - [e5]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk:
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2017, Como, Italy, August 27, 2017. ACM 2017, ISBN 978-1-4503-5353-3 [contents] - [i10]Hagit Grushka-Cohen, Oded Sofer, Ofer Biller, Michael Dymshits, Lior Rokach, Bracha Shapira:
Sampling High Throughput Data for Anomaly Detection of Data-Base Activity. CoRR abs/1708.04278 (2017) - [i9]Yael Brumer, Bracha Shapira, Lior Rokach, Oren Barkan:
Predicting Relevance Scores for Triples from Type-Like Relations using Neural Embedding - The Cabbage Triple Scorer at WSDM Cup 2017. CoRR abs/1712.08359 (2017) - 2016
- [j40]Lihi Naamani Dery, Meir Kalech, Lior Rokach, Bracha Shapira:
Reducing preference elicitation in group decision making. Expert Syst. Appl. 61: 246-261 (2016) - [j39]David Ben-Shimon, Lior Rokach, Bracha Shapira:
An ensemble method for top-N recommendations from the SVD. Expert Syst. Appl. 64: 84-92 (2016) - [j38]Moshe Unger, Ariel Bar, Bracha Shapira, Lior Rokach:
Towards latent context-aware recommendation systems. Knowl. Based Syst. 104: 165-178 (2016) - [j37]Edita Grolman, Ariel Bar, Bracha Shapira, Lior Rokach, Aviram Dayan:
Utilizing transfer learning for in-domain collaborative filtering. Knowl. Based Syst. 107: 70-82 (2016) - [j36]Moran Beladev, Lior Rokach, Bracha Shapira:
Recommender systems for product bundling. Knowl. Based Syst. 111: 193-206 (2016) - [j35]David Ben-Shimon, Lior Rokach, Guy Shani, Bracha Shapira:
Anytime Algorithms for Recommendation Service Providers. ACM Trans. Intell. Syst. Technol. 7(3): 43:1-43:26 (2016) - [c52]Ariel Bar, Bracha Shapira, Lior Rokach, Moshe Unger:
Scalable attack propagation model and algorithms for honeypot systems. IEEE BigData 2016: 1130-1135 - [c51]Yisroel Mirsky, Asaf Shabtai, Lior Rokach, Bracha Shapira, Yuval Elovici:
SherLock vs Moriarty: A Smartphone Dataset for Cybersecurity Research. AISec@CCS 2016: 1-12 - [c50]Hagit Grushka-Cohen, Oded Sofer, Ofer Biller, Bracha Shapira, Lior Rokach:
CyberRank: Knowledge Elicitation for Risk Assessment of Database Security. CIKM 2016: 2009-2012 - [c49]Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach:
RecSys'16 Workshop on Deep Learning for Recommender Systems (DLRS). RecSys 2016: 415-416 - [c48]Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar:
Deep Auto-Encoding for Context-Aware Inference of Preferred Items' Categories. RecSys Posters 2016 - [c47]Ariel Bar, Bracha Shapira, Lior Rokach, Moshe Unger:
Identifying Attack Propagation Patterns in Honeypots Using Markov Chains Modeling and Complex Networks Analysis. SwSTE 2016: 28-36 - [e4]Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach:
Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2016, Boston, MA, USA, September 15, 2016. ACM 2016, ISBN 978-1-4503-4795-2 [contents] - [i8]Victor Makarenkov, Bracha Shapira, Lior Rokach:
Language Models with GloVe Word Embeddings. CoRR abs/1610.03759 (2016) - 2015
- [j34]Gilad Katz, Nir Ofek, Bracha Shapira:
ConSent: Context-based sentiment analysis. Knowl. Based Syst. 84: 162-178 (2015) - [c46]Yasmin Bokobza, Abigail Paradise, Guy Rapaport, Rami Puzis, Bracha Shapira, Asaf Shabtai:
Leak Sinks: The Threat of Targeted Social Eavesdropping. ASONAM 2015: 375-382 - [c45]Dmitri Bekerman, Bracha Shapira, Lior Rokach, Ariel Bar:
Unknown malware detection using network traffic classification. CNS 2015: 134-142 - [c44]David Ben-Shimon, Lior Rokach, Bracha Shapira, Guy Shani:
Fast Item-Based Collaborative Filtering. ICAART (2) 2015: 457-463 - [c43]Victor Makarenkov, Bracha Shapira, Lior Rokach:
Theoretical Categorization of Query Performance Predictors. ICTIR 2015: 369-372 - [c42]Nir Ofek, Gilad Katz, Bracha Shapira, Yedidya Bar-Zev:
Sentiment Analysis in Transcribed Utterances. PAKDD (2) 2015: 27-38 - [c41]Yisroel Mirsky, Bracha Shapira, Lior Rokach, Yuval Elovici:
pcStream: A Stream Clustering Algorithm for Dynamically Detecting and Managing Temporal Contexts. PAKDD (2) 2015: 119-133 - [c40]Moran Beladev, Bracha Shapira, Lior Rokach:
Recommender Systems for Product Bundling. RecSys Posters 2015 - [c39]Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann:
In-House Solution for the RecSys Challenge 2015. RecSys Challenge 2015: 10:1-10:4 - [c38]Nofar Dali Betzalel, Bracha Shapira, Lior Rokach:
"Please, Not Now!": A Model for Timing Recommendations. RecSys 2015: 297-300 - [c37]David Ben-Shimon, Alexander Tsikinovsky, Michael Friedmann, Bracha Shapira, Lior Rokach, Johannes Hoerle:
RecSys Challenge 2015 and the YOOCHOOSE Dataset. RecSys 2015: 357-358 - [c36]Bracha Shapira, Nir Ofek, Victor Makarenkov:
Exploiting Wikipedia for Information Retrieval Tasks. SIGIR 2015: 1137-1140 - [c35]Yisroel Mirsky, Aviad Cohen, Roni Stern, Ariel Felner, Lior Rokach, Yuval Elovici, Bracha Shapira:
Search Problems in the Domain of Multiplication: Case Study on Anomaly Detection Using Markov Chains. SOCS 2015: 70-77 - [c34]Mordechai Guri, Yuri Poliak, Bracha Shapira, Yuval Elovici:
JoKER: Trusted Detection of Kernel Rootkits in Android Devices via JTAG Interface. TrustCom/BigDataSE/ISPA (1) 2015: 65-73 - [e3]David Ben-Shimon, Michael Friedmann, Lior Rokach, Bracha Shapira:
Proceedings of the 2015 International ACM Recommender Systems Challenge, RecSys Challenge 2015, Vienna, Austria, September 16-20, 2015. ACM 2015, ISBN 978-1-4503-3665-9 [contents] - [e2]Francesco Ricci, Lior Rokach, Bracha Shapira:
Recommender Systems Handbook. Springer 2015, ISBN 978-1-4899-7636-9 [contents] - [r1]Francesco Ricci, Lior Rokach, Bracha Shapira:
Recommender Systems: Introduction and Challenges. Recommender Systems Handbook 2015: 1-34 - [i7]Gilad Katz, Bracha Shapira:
Enabling Complex Wikipedia Queries - Technical Report. CoRR abs/1508.03298 (2015) - [i6]Mordechai Guri, Yuri Poliak, Bracha Shapira, Yuval Elovici:
JoKER: Trusted Detection of Kernel Rootkits in Android Devices via JTAG Interface. CoRR abs/1512.04116 (2015) - 2014
- [j33]Asaf Shabtai, Lena Tenenboim-Chekina, Dudu Mimran, Lior Rokach, Bracha Shapira, Yuval Elovici:
Mobile malware detection through analysis of deviations in application network behavior. Comput. Secur. 43: 1-18 (2014) - [j32]Gilad Katz, Yuval Elovici, Bracha Shapira:
CoBAn: A context based model for data leakage prevention. Inf. Sci. 262: 137-158 (2014) - [j31]