2018

  1. Zablocki, É., Piwowarski, B., Soulier, L., & Gallinari, P. (2018). Learning Multi-Modal Word Representation Grounded in Visual Context. In Proceedings of the Association for the Advancement of Artificial Intelligence.
  2. Santos, L. D., Piwowarski, B., Denoyer, L., & Gallinari, P. (2018). Representation Learning for Classification in Heterogeneous Graphs with Application to Social Networks. ACM Trans. Knowl. Discov. Data, 12(5), 62:1–62:33. https://doi.org/10/gdvmmq
  3. Titeux, H., Piwowarski, B., & Gallinari, P. (2018). Représentations Gaussiennes Pour Le Filtrage Collaboratif. In Conférence En Recherche d’Information et Applications.
  4. Lopez-Rincon, A., Tonda, A., Elati, M., Schwander, O., Piwowarski, B., & Gallinari, P. (2018). Evolutionary Optimization of Convolutional Neural Networks for Cancer miRNA Biomarkers Classification. Applied Soft Computing, 65, 91–100. https://doi.org/10/gcwbsh

2017

  1. Dos Santos, L., Piwowarski, B., & Gallinari, P. (2017). Gaussian Embeddings for Collaborative Filtering. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1065–1068). New York, NY, USA: ACM. https://doi.org/10.1145/3077136.3080722
  2. Zablocki, É., Bordes, P., Soulier, L., Piwowarski, B., & Gallinari, P. (2017). LIP6@CLEF2017: Multi-Modal Spatial Role Labeling Using Word Embeddings Working Notes. In CLEF. Dublin, Ireland.

2016

  1. Ziat, A., Denoyer, L., Piwowarski, B., Gallinari, P., & Ziat, A. (2016). Modeling Relational Time Series Using Gaussian Embeddings. In NIPS Time Series Workshop.
  2. Dos Santos, L., Piwowarski, B., & Gallinari, P. (2016). Multilabel Classification on Heterogeneous Graphs with Gaussian Embeddings. In ECML (pp. 606–622). Springer International Publishing. https://doi.org/10.1007/978-3-319-46227-1_38
  3. Singh, G., & Piwowarski, B. (2016). Efficient Document Indexing Using Pivot Tree. arXiv.
  4. Despres, N., Lamprier, S., & Piwowarski, B. (2016). Apprentissage de Modèles de Langue Neuronaux Pour La Recherche d’Information. In Conférence En Recherche d’Infomations et Applications.
  5. Kraljevic, Z., Baskiotis, N., Piwowarski, B., & Gallinari, P. (2016). Représentation Temporelle Des Mots : Application Au Clustering de Micro-Blogs. In Conférence En Recherche d’Infomations et Applications (pp. 531–544).
  6. Piwowarski, B. (2016). Learning Term Weights for Ad-Hoc Retrieval (No. 1606.04223v1).

2015

  1. Piwowarski, B., Lamprier, S., & Despres, N. (2015). Parameterized Neural Network Language Models for Information Retrieval. arXiv.
  2. Gauthier, L. A., Piwowarski, B., & Gallinari, P. (2015). Leveraging Rating Behavior to Predict Negative Social Ties. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 623–628). https://doi.org/10.1145/2808797.2809402
  3. Gauthier, L.-A. (2015). Inférence de Liens Signés Dans Les Réseaux Sociaux, Par Apprentissage à Partir d’interactions Utilisateur. In Conférence En Recherche d’Infomations et Applications.
  4. Dos Santos, L., Piwowarski, B., & Gallinari, P. (2015). Graph Based Method Approach to the ImageCLEF2015 Task1 - Image Annotation. In L. Cappellato, N. Ferro, G. J. F. Jones, & E. SanJuan (Eds.), CLEF2015 Task1 - Image Annotation CEUR Workshop Proceedings. CEUR-WS.org.
  5. Gauthier, L.-A., Piwowarski, B., & Gallinari, P. (2015). Polarité Des Jugements et Des Interactions Pour Le Filtrage Collaboratif et La Prédiction de Liens Sociaux. In Conférence En Recherche d’Informations et Applications (pp. 139–154). Paris, France. https://doi.org/10.24348/coria.2015.81

2014

  1. Gauthier, L.-A., Piwowarski, B., & Gallinari, P. (2014). Filtrage Collaboratif et Intégration de La Polarité Des Notes. In Conférence En Recherche d’Infomations et Applications.

2013

  1. Dupret, G., & Piwowarski, B. (2013). Model Based Comparison of Discounted Cumulative Gain and Average Precision. Journal of Discrete Algorithms, 49–62. https://doi.org/10.1016/j.jda.2012.10.002
  2. Pehlivan, Z., Piwowarski, B., & Gançarski, S. (2013). Diversification Based Static Index Pruning - Application to Temporal Collections (No. 1308.4839v1).
  3. Pehlivan, Z., Piwowarski, B., & Gançarski, S. (2013). A Comparison of Static Index Pruning Methods with Temporal Queries. In SIGIR 2013 Workshop on Time-Aware Information Access. LIP6.
  4. Piwowarski, B. (2013). Méthodologie Pour Une Représentation Multi-Dimensionnelle Des Documents. In Conférence En Recherche d’Infomations et Applications.

2012

  1. Piwowarski, B. (2012). The Kernel Quantum Probabilities (KQP) Library (No. 1203.6005v2).
  2. Piwowarski, B., Amini, M.-R., & Lalmas, M. (2012). On Using a Quantum Physics Formalism for Multidocument Summarization. Journal of the American Society for Information Science and Technology, 63, 865–888. https://doi.org/10.1002/asi.21713
  3. Piwowarski, B., Dupret, G., & Lalmas, M. (2012). Beyond Cumulated Gain and Average Precision: Including Willingness and Expectation in the User Model (No. 1209.4479v1).

2011

  1. Frommholz, I., Piwowarski, B., Lalmas, M., & Rijsbergen, K. (2011). Processing Queries in Session in a Quantum-Inspired IR Framework. In Proceedings of the 33rd European Conference on Advances in Information Retrieval.
  2. Moshfeghi, Y., Piwowarski, B., & Jose, J. (2011). Handling Data Sparsity in Collaborative Filtering Using Emotion and Semantic Based Features. In Proceedings of the 34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM.
  3. Attfield, S., Kazai, G., Lalmas, M., & Piwowarski, B. (2011). Towards a Science of User Engagement (Position Paper). In WSDM Workshop on User Modelling for Web Applications.
  4. Caputo, A., Piwowarski, B., & Lalmas, M. (2011). A Query Algebra for Quantum Information Retrieval. In Proceedings of the 2nd Italian Information Retrieval Workshop.
  5. Zuccon, G., Piwowarski, B., & Azzopardi, L. (2011). On the Use of Complex Numbers in Quantum Models for Information Retrieval. In ECIR (pp. 346–350). https://doi.org/10.1007/978-3-642-23318-0_36
  6. Piwowarski, B., & Blanco, R. (2011). Introducción a La Recuperación de Información. In F. C. Sijo, J. M. F. Luna, & J. F. H. Guadix (Eds.). RA-MA.

2010

  1. Piwowarski, B., Frommholz, I., Lalmas, M., & Rijsbergen, K. (2010). What Can Quantum Theory Bring to IR? In J. Huang, N. Koudas, G. Jones, X. Wu, K. Collins-Thompson, & A. An (Eds.), Proceedings of the Nineteenth ACM Conference on Conference on Information and Knowledge Management. ACM. https://doi.org/10.1145/1871437.1871450
  2. Piwowarski, B., Frommholz, I., Moshfeghi, Y., Lalmas, M., & Rijsbergen, K. (2010). Filtering Documents with Subspaces. In C. Gurrin, Y. He, G. Kazai, U. Kruschwitz, S. Little, T. Roelleke, … K. van Rijsbergen (Eds.), ECIR (Vol. 5993). Springer.
  3. Piwowarski, B., Frommholz, I., Lalmas, M., & Rijsbergen, K. (2010). Exploring a Multidimensional Representation of Documents and Queries (Extended Version) (arXiv).
  4. Piwowarski, B., Frommholz, I., Lalmas, M., & Rijsbergen, K. (2010). Exploring a Multidimensional Representation of Documents and Queries. In Proceedings of Recherche d’Information Assistée Par Ordinateur.
  5. Sushmita, S., Piwowarski, B., & Lalmas, M. (2010). Dynamics of Genre and Domain Intents. In Asia Information Retrieval Symposium (Vol. 6548).
  6. Frommholz, I., Larsen, B., Piwowarski, B., Lalmas, M., Ingwersen, P., & Rijsbergen, K. (2010). Supporting Polyrepresentation in a Quantum-Inspired Geometrical Retrieval Framework. In Proceedings of the Third Symposium on Information Interaction in Context. New Brunswick, NJ, USA. https://doi.org/10.1145/1840784.1840802
  7. Dupret, G., & Piwowarski, B. (2010). A User Behavior Model for Average Precision and Its Generalization to Graded Judgments. In F. Crestania, S. Marchand-Maillet, H.-H. Chen, E. N. Efthimiadis, & J. Savoy (Eds.), Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM.

2009

  1. Pehcevski, J., & Piwowarski, B. (2009). Evaluation Metrics for Structured Text Retrieval. Encyclopedia of Database Systems. Boston, MA: Springer US. https://doi.org/10.1007/978-0-387-39940-9_152
  2. Piwowarski, B., & Lalmas, M. (2009). Structured Information Retrieval and Quantum Theory. In P. Bruza, D. Sofge, W. Lawless, K. van Rijsbergen, & M. Klusch (Eds.), Proceedings of the 3rd QI Symposium (Vol. 5494). Springer.
  3. Pehcevski, J., & Piwowarski, B. (2009). Specificity. Encyclopedia of Database Systems. Boston, MA: Springer US.
  4. Piwowarski, B., & Dupret, G. (2009). System and Method for Deducing User Interaction Patterns Based on Limited Activities.
  5. Piwowarski, B., & Zaragoza, H. (2009). System and Method for Creating and Applying Predictive User Click Models to Predict a Target Page Associated with a Search Query.
  6. Piwowarski, B., Trotman, A., & Lalmas, M. (2009). Sound and Complete Relevance Assessments for XML Retrieval. Transactions On Information Systems, 27(1).
  7. Fernández-Luna, J., Huete, J., & Piwowarski, B. (2009). Introduction to the Special Issue on Graphical Models and Information Retrieval. International Journal of Approximate Reasoning, 50(7), 929–931.
  8. Piwowarski, B., & Lalmas, M. (2009). A Quantum-Based Model for Interactive Information Retrieval (Extended Version). In arXiv.Org. arXiv.
  9. Piwowarski, B., & Lalmas, M. (2009). A Quantum-Based Model for Interactive Information Retrieval. In L. Azzopardi, G. Kazai, S. E. Robertson, S. M. Rüger, M. Shokouhi, & D. Song (Eds.), Proceeedings of the 2nd International Conference on the Theory of Information Retrieval (Vol. 5766). Cambridge, United Kingdom: Springer.
  10. Moshfeghi, Y., Agarwal, D., Piwowarski, B., & Jose, J. (2009). Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering Lecture Notes in Computer Science. In M. Boughanem, C. Berrut, J. Mothe, & C. Soulé-Dupuy (Eds.), Proceedings of the 31th European Conference on Information Retrieval Conference (pp. 54–65). Toulouse, France: Springer. https://doi.org/10.1007/978-3-642-00958-7_8
  11. Piwowarski, B., Dupret, G., & Jones, R. (2009). Mining User Web Search Activity with Layered Bayesian Networks or How to Capture a Click in Its Context. In R. A. Baeza-Yates, P. Boldi, B. A. Ribeiro-Neto, & B. B. Cambazoglu (Eds.), Proceedings of the Second ACM International Conference on Web Search and Data Mining (pp. 162–171). Barcelona, Spain: ACM. https://doi.org/10.1145/1498759.1498823

2008

  1. Dupret, G., & Piwowarski, B. (2008). A User Browsing Model to Predict Search Engine Click Data from Past Observations. In S.-H. Myaeng, F. Sebastiani, T.-S. Chua, & M.-K. Leong (Eds.), Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Singapore: ACM.

2007

  1. Motelet, O., Baloian, N., Piwowarski, B., & Pino, J. (2007). Taking Advantage of the Semantics of a Lesson Graph Based on Learning Objects. In The 13th International Conference on Artificial Intelligence in Education. IOS Press.
  2. Kazai, G., Piwowarski, B., & Robertson, S. E. (2007). Effort Precision and Gain-Recall Based on a Probabilistic Navigation Model. In 1st International Conference on the Theory of Information Retrieval.
  3. Piwowarski, B., & Zaragoza, H. (2007). Predictive User Click Models Based on Click-through History. In Proceedings of the 16th ACM International Conference on Information and Knowledge Management (pp. 175–182). Lisbon, Portugal: ACM.
  4. Motelet, O., Piwowarski, B., Dupret, G., Pino, J., & Baloian, N. (2007). Enhancing Educational-Material Retrieval Using Authored-Lesson Metadata. In Fourteenth String Processing and Information Retrieval Symposium. Santiago, Chile.
  5. Dupret, G., Murdock, V., & Piwowarski, B. (2007). Web Search Engine Evaluation Using Clickthrough Data and a User Model. In Query Log Analysis: Social and Technological Challenges.
  6. Piwowarski, B., Gallinari, P., & Dupret, G. (2007). An Extension of Precision-Recall with User Modelling (PRUM): Application to XML Retrieval. ACM Transactions On Information Systems, 25(1). https://doi.org/10.1145/1198296.1198297

2006

  1. Piwowarski, B., & Dupret, G. (2006). Evaluation in (XML) Information Retrieval: Expected Precision-Recall with User Modelling (EPRUM). In E. N. Efthimiadis, S. T. Dumais, D. Hawking, & K. Järvelin (Eds.), Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 260–267). Seattle, Washington, USA: ACM. https://doi.org/10.1145/1148170.1148218
  2. Bast, H., Dupret, G., Majumdar, D., & Piwowarski, B. (2006). Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis. In M. Ackermann, B. Berendt, M. Grobelnik, A. Hotho, D. Mladenic, G. Semeraro, … M. van Someren (Eds.), Semantics, Web and Mining, Joint International Workshops, EWMF 2005 and KDO 2005 (pp. 103–120). Porto, Portugal: Springer.
  3. Dupret, G., & Piwowarski, B. (2006). Principal Components for Automatic Term Hierarchy Building. In Proceedings of the 13th International Symposium on String Processing and Information Retrieval (pp. 37–48). Springer.
  4. Dupret, G., Piwowarski, B., Hurtado, C., & Mendoza, M. (2006). A Statistical Model of Query Log Generation. In Proceedings of the 13th International Symposium on String Processing and Information Retrieval (pp. 217–228). Springer.

2005

  1. Piwowarski, B., & Gallinari, P. (2005). A Bayesian Network for XML Information Retrieval: Searching and Learning with the INEX Collection. In Proceedings of the Initiative for the Evaluation of XML Retrieval (pp. 655–681). https://doi.org/10.1007/s10791-005-0751-6

2004

  1. Vu, H.-T., Piwowarski, B., & Gallinari, P. (2004). Filtering in XML Retrieval: A Prospective Analysis. University of Sheffield, UK.
  2. Piwowarski, B., & Lalmas, M. (2004). Interface Pour l’évaluation de Systèmes de Recherche Sur Des Documents XML. In Premiere COnference En Recherche d’Information et Applications. Toulouse, France.
  3. Piwowarski, B., & Lalmas, M. (2004). Providing Consistent and Exhaustive Relevance Assessments for XML Retrieval Evaluation. In Proceedings of the Thirteenth Conference on Information and Knowledge Management. Washington D.C., U.S.A. https://doi.org/10.1145/1031171.1031246
  4. Piwowarski, B., & Gallinari, P. (2004). An Algebra for Probabilistic XML Retrieval. In 1st Twente Data Management Workshop on XML Databases and Information Retrieval. Enschede, The Netherlands: SIKS.

2003

  1. Piwowarski, B., & Gallinari, P. (2003). Expected Ratio of Relevant Units: A Measure for Structured Information Retrieval. In N. Fuhr, M. Lalmas, & S. Malik (Eds.), Proceedings of the Second INEX Workshop. Dagstuhl, France.
  2. Piwowarski, B., Vu, H.-T., & Gallinari, P. (2003). Bayesian Networks and INEX’03. In N. Fuhr, M. Lalmas, & S. Malik (Eds.). Dagstuhl, Germany.
  3. Piwowarski, B., & Gallinari, P. (2003). Structure, Recherche d’information et Apprentissage. In Conférence Extraction et Gestion Des Connaissances. Lyon, France.
  4. Kazai, G., Lalmas, M., & Piwowarski, B. (2003). INEX Guidelines for Topic Development. In N. Fuhr, M. Lalmas, & S. Malik (Eds.).
  5. Piwowarski, B., & Gallinari, P. (2003). A Machine Learning Model for Information Retrieval with Structured Documents. In P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition (pp. 425–438).
  6. Piwowarski, B. (2003). Working Group Report: The Assessment Tool. In N. Fuhr, M. Lalmas, & S. Malik (Eds.), INEX Proceedings. Dagstuhl, Germany.
  7. Piwowarski, B. (2003). Techniques d’apprentissage Pour Le Traitement d’informations Structurées : Application à La Recherche d’information (PhD thesis). University Paris 6, Paris, France.

2002

  1. Piwowarski, B., Faure, G.-E., & Gallinari, P. (2002). Bayesian Networks and INEX. In Proceedings of the First Annual Workshop of the Initiative for the Evaluation of XML Retrieval. Dagstuhl, Germany: ERCIM.
  2. Denoyer, L., Piwowarski, B., & Gallinari, P. (2002). Un Modèle Pour La Recherche d’information Sur Des Documents Structurés. In JADT. Saint-Malo, France.
  3. Piwowarski, B., & Gallinari, P. (2002). A Bayesian Network Model for Page Retrieval in a Hierarchically Structured Collection. In XML Workshop of the 25th ACM SIGIR Conference. Tampere, Finland.

2000

  1. Piwowarski, B. (2000). Learning in Information Retrieval: A Probabilistic Differential Approach. In Proceedings of the BCS-IRSG, 22nd Annual Colloquium on Information Retrieval Research. Sidney Sussex College, Cambridge, England.
  2. Piwowarski, B. (2000). Apprentissage et Recherche Documentaire : Une Approche Probabiliste Différentielle. In Colloque Francophone Sur l’Apprentissage Automatique. Saint-Etienne, France.