Prof. Maayan Zhitomirsky-Geffet
2020 - present: Associate Professor, Information Science Department
2016-2020: Senior Lecturer, Bar-Ilan University, Information Science Department
2006-2016: Lecturer, Bar-Ilan University, Information Science Department
Post-Doctoral Research Associate, Computer Science Dept. Bar-Ilan University, 2006.
Research project in the area of Semantic Information Retrieval, funded by the Israeli Ministry of Defense.
Supervisor: Prof. Ido Dagan.
Ph.D., Computer Science in the area of Computational Linguistics and Statistical Natural Language Processing, The Hebrew University in Jerusalem, 2006.
Thesis: Refining the Distributional Similarity Scheme for Lexical Entailment
Prof. Ido Dagan, Computer Science Department, Bar-Ilan University,
Prof. Dror G. Feitelson, School of Computer Science and Engineering, The Hebrew University
M.Sc., Computer Science in the area of Information Retrieval, The Hebrew University in Jerusalem (Magna Cum Laude), 2000.
Thesis: Automatic Hierarchical Indexing and Document Classification
Supervisor: Prof. Dror G. Feitelson, School of Computer Science and Engineering, The Hebrew University
B.Sc., Computer Science, BA- Linguistics - Magna Cum Laude, The Hebrew University in Jerusalem, 1998.
Journal of the American Society for Information Science and Technology
Journal of Engineering and Computer Innovation
Information Technology Research Journal
Coling Internation Conference for Computational Linguistics
Marital Status: Married to Benjamin and mother to Elhanan Shmuel, Yael, Rachel and Noam Yosef
Languages: Hebrew, Russian, English.
The ethical data-driven research lab
Maayan Zhitomirsky-Geffet received her PhD in natural language processing from the Hebrew University of Jerusalem (2006). In the past decade, she has been leading the field of ethical data-driven research in the Department of Information Science at Bar Ilan University. Dr. Zhitomirsky-Geffet has developed the ethical approach to representing, organizing and analyzing information based on multi-viewpoint ontologies. Her research deals with the development of ethical ontological models that serve as a tool for identifying and analyzing opinions and assessing biases in large textual corpora. The ethical approach may help identify various types of biases in the data (e.g. cultural, gender-oriented, religious, political, temporal, and more) in various domains (e.g., art, historical literature, politics, labor market, online personal branding, communication, academic promotion and influence, education) and balancing them by increasing the diversity of voices in knowledge representation and harmonization of different perspectives.
According to this approach, artificial intelligence algorithms will present the user with relevant information based on the "related yet different or complementary information" relevance criterion that allows for diversity, inclusion and balance rather than on the criterion of similarity to the previous content in which a user was engaged. That is, retrieval and personalization of information will be done on the basis of relevance defined as information that is “related yet different” in order to broaden the horizons of the user in the subject of his interest rather than narrowing his vision and views. This approach can neutralize the “rich getting richer” effect on the web that causes distortions and biases in the ranking of information importance by algorithms and ultimately also by humans who are exposed to these automatic rankings directly or indirectly. This ethical and inclusive approach to the organization and retrieval of information aims to prevent the spread and increase of the influence of hate content and fake news on the Internet, and thus also to prevent social polarization and even harm to democracy and civil war. Dr. Zhitomirsky-Geffet's laboratory also investigates other aspects of ethics in the use of technology, such as the application of multi-viewpoint ontological models for quantitative analysis (remote reading) of corpora in the humanities and social sciences, online user privacy and addiction to information technology.
Prof. Zhitomirsky-Geffet is a research partner in the European Time Machine Project, with the aim of building a multi-viewpoint ontology for Jerusalem and other multicultural cities, in the Jerusalem National Knowledge Center of the Ministry of Science, and in the European CSI-COP Project “citizen scientists investigating trackers on the web”. She also serves as a chair of the ethics committee of the Humanities and Jewish studies faculties in Bar-Ilan University.
Yigal Maman, 2013
Real-estate ontology construction for market trend detection and user behavior analysis on the Israeli real-estate web sites
Yossi Daya, 2014
Extracting sub-topics and re-ranking search engine’s query results using social bookmarking and social tagging systems
Yair Bratspiess, 2014
Professional information disclosure on social networks and their effectiveness for finding a job: the case of Facebook and LinkedIn in Israel
Hodaya Uzan, 2014
Utilizing posts from public Facebook profiles and political pages to automatically predict the political stance of their authors (with Prof. Moshe Koppel and Dr. Ester David),
Orna Bloch, 2015
Improving proverb search and retrieval with a generic multidimensional ontology (with Dr. Gila Prebor)
Maya Blau, 2016
Cross-generational analysis of predictive factors of addictive behavior in smartphone usage
Haim Mograbi, 2016
Development of a methodology for guided construction of ontology by domain experts and information scientists: the case of pests in agriculture
Avital Zadok, 2016
Risk analysis and prediction in welfare institutions using a dedicated expert system
Maor Weinberger, 2016
User online anonymity awareness among students (with Prof. Dan Bouhnik)
Golan Avidan, 2019
Modelling multi-viewpoint and multi-theory ontologies
Avraham Weic, 2019
Sectorial differences in job-hunting perceptions and behavior in social networks in Israel
Shir Hillel, 2019
Towards a wider perspective in the social sciences using a network of variables based on thousands of results (with Dr. Ofer Bergman)
Omri Suissa, 2019
A neural network approach for generating a training corpus for OCR post-processing error correction for historical newspaper corpus (with Dr. Avshalom Elmalech)
Shai Shlomo Eistein, 2019
Browser search hijackers (with Prof. Dan Bouhnik)
Sarah Minster, 2021
Biases in digital culture collections - developing a new approach for automatic evaluation based on Wikidata
Gal Oz, 2022
The discourse changes on Facebook of politicians in Israel during the four consecutive election campaigns in the years 2019-2021 (with Dr. Avshalom Elmalech and in collaboration with Dr. Jonathan Schler)
Maor Weinberger, 2021
Developing a model for assessing and predicting academic influence based on the citation graph structure
Avital Tzadok, 2022
Automatic construction and comparative analysis of networks between the Jewish sages in the texts of Mishnah and Tosefta (in collaboration with Dr. Binyamin Katzoff)
Omri Suissa, 2022
Developing deep neural network models to answer natural language questions on a large genealogical corpus (joint guidance with Dr. Avshalom Elmalech)
Nati Ben Gigi, 2024
Automatic construction and analysis of local and global citation networks in the Jewish responsa literature using machine learning methods (joint guidance with Dr. Jonathan Schler and in collaboration with Dr. Binyamin Katzoff)
Efrat Miller, 2024
Building a multi-viewpoint ontology as a tool for analyzing differences between countries in UN speeches over time (joint guidance with Dr. Mor Mitteraney as part of the ISF-funded Talking States project)
Sara Minster, 2024
Semi-automatic classification of multi-viewpoint texts based on diverse similarity and Wikidata as a multi-viewpoint ontology
Course no. 35-728: Introduction to Databases
Course no. 35-730: Web Site Construction in HTML and CSS
Course no. 35-746: Seminar on Semantic Web Technologies
Course no. 35-867: Programming in C#
Course no. 35-879: Introduction to the Semantic Web
Chapters in Books
Department of Information Science,
Ramat Gan, Israel
Last Updated Date : 08/06/2022