D-Index & Metrics Best Publications
Mounia Lalmas

Mounia Lalmas

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 54 Citations 8,508 262 World Ranking 2362 National Ranking 10

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • World Wide Web
  • Information retrieval

Mounia Lalmas spends much of her time researching Information retrieval, Relevance, Human–computer information retrieval, XML and Human–computer interaction. Her work on Ranking as part of general Information retrieval study is frequently linked to Rank, bridging the gap between disciplines. She interconnects Document retrieval, Ranking, Query expansion and Structured document in the investigation of issues within Relevance.

Her work deals with themes such as Visual Word, Vector space model and Data retrieval, which intersect with Human–computer information retrieval. Her XML research includes themes of Dependency, Paragraph and Stability. Her work on Computer user satisfaction, User experience design and User journey is typically connected to Mouse tracking as part of general Human–computer interaction study, connecting several disciplines of science.

Her most cited work include:

  • A survey on the use of relevance feedback for information access systems (374 citations)
  • Sound and complete relevance assessment for XML retrieval (228 citations)
  • “Is this document relevant?…probably”: a survey of probabilistic models in information retrieval (197 citations)

What are the main themes of her work throughout her whole career to date?

Mounia Lalmas focuses on Information retrieval, World Wide Web, Relevance, XML and XML retrieval. Her Information retrieval research is multidisciplinary, relying on both XML validation and Document Structure Description. In the field of World Wide Web, her study on Search engine and Social media overlaps with subjects such as User engagement and Reading.

Her study in Relevance is interdisciplinary in nature, drawing from both Query expansion, Representation, Information needs and Relevance feedback. The various areas that Mounia Lalmas examines in her Human–computer information retrieval study include Concept search and Data retrieval. The study incorporates disciplines such as Vector space model and Document clustering in addition to Document retrieval.

She most often published in these fields:

  • Information retrieval (57.89%)
  • World Wide Web (26.90%)
  • Relevance (18.42%)

What were the highlights of her more recent work (between 2014-2021)?

  • World Wide Web (26.90%)
  • Recommender system (5.26%)
  • Information retrieval (57.89%)

In recent papers she was focusing on the following fields of study:

The scientist’s investigation covers issues in World Wide Web, Recommender system, Information retrieval, User engagement and Artificial intelligence. Her World Wide Web research incorporates elements of Variety and User experience design. Her Recommender system research includes elements of Homophily and Service.

Her primary area of study in Information retrieval is in the field of Ranking. Mounia Lalmas has included themes like Machine learning, Digital content and Natural language processing in her Artificial intelligence study. Her biological study spans a wide range of topics, including Cluster analysis and Pattern recognition.

Between 2014 and 2021, her most popular works were:

  • Towards a Fair Marketplace: Counterfactual Evaluation of the trade-off between Relevance, Fairness & Satisfaction in Recommendation Systems (82 citations)
  • Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking (80 citations)
  • Understanding User Attention and Engagement in Online News Reading (57 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • World Wide Web
  • The Internet

Her primary scientific interests are in World Wide Web, Recommender system, Set, User engagement and Focus. As part of her studies on World Wide Web, she often connects relevant areas like Quality. Her research integrates issues of Variety, Homophily and Human–computer interaction in her study of Recommender system.

Mounia Lalmas combines subjects such as User experience design and Page view with her study of Set. Her User experience design research is multidisciplinary, incorporating perspectives in Digital media and Online advertising. Her Dwell time study spans across into fields like Quality rating, Information retrieval, Survival analysis, Metric and Bounce rate.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A survey on the use of relevance feedback for information access systems

Ian Ruthven;Mounia Lalmas.
Knowledge Engineering Review (2003)

545 Citations

“Is this document relevant?…probably”: a survey of probabilistic models in information retrieval

Fabio Crestani;Mounia Lalmas;Cornelis J. Van Rijsbergen;Iain Campbell.
ACM Computing Surveys (1998)

345 Citations

Models of user engagement

Janette Lehmann;Mounia Lalmas;Elad Yom-Tov;Georges Dupret.
international conference on user modeling adaptation and personalization (2012)

272 Citations

Sound and complete relevance assessment for XML retrieval

Benjamin Piwowarski;Andrew Trotman;Mounia Lalmas.
ACM Transactions on Information Systems (2008)

228 Citations

Advances in XML Information Retrieval and Evaluation

Norbert Fuhr;Mounia Lalmas;Saadia Malik;Gabriella Kazai.
(2006)

183 Citations

Measuring User Engagement

Mounia Lalmas;Heather O'Brien;Elad Yom-Tov.
(2014)

180 Citations

Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers

Norbert Fuhr;Jaap Kamps;Mounia Lalmas;Andrew Trotman.
Lecture Notes in Computer Science (2008)

177 Citations

Dempster-Shafer's theory of evidence applied to structured documents: modelling uncertainty

Mounia Lalmas.
international acm sigir conference on research and development in information retrieval (1997)

174 Citations

The overlap problem in content-oriented XML retrieval evaluation

Gabriella Kazai;Mounia Lalmas;Arjen P. de Vries.
international acm sigir conference on research and development in information retrieval (2004)

140 Citations

Comparative Evaluation of XML Information Retrieval Systems: 5th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2006 Dagstuhl Castle, Germany, December 17-20, 2006 Revised and Selected Papers

Norbert Fuhr;Mounia Lalmas;Andrew Trotman.
(2005)

132 Citations

Best Scientists Citing Mounia Lalmas

Jaap Kamps

Jaap Kamps

University of Amsterdam

Publications: 53

Maarten de Rijke

Maarten de Rijke

University of Amsterdam

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Dawei Song

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Beijing Institute of Technology

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Ralf Schenkel

Ralf Schenkel

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Fabio Crestani

Fabio Crestani

Universita della Svizzera Italiana

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Djoerd Hiemstra

Djoerd Hiemstra

Radboud University Nijmegen

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Gabriella Pasi

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University of Milano-Bicocca

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Gerhard Weikum

Gerhard Weikum

Max Planck Institute for Informatics

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Luis M. de Campos

Luis M. de Campos

University of Granada

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Norbert Fuhr

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University of Duisburg-Essen

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Krisztian Balog

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University of Stavanger

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Gabriella Kazai

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Microsoft (United States)

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Peter Bruza

Peter Bruza

Queensland University of Technology

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Bernard J. Jansen

Bernard J. Jansen

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Filippo Menczer

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W. Bruce Croft

W. Bruce Croft

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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