All Outputs (17)

Can we predict QPP? An approach based on multivariate outliers (2024)
Conference Proceeding
Chifu, A., Déjean, S., Garouani, M., Mothe, J., Ortiz, D., & Ullah, M. Z. (2024). Can we predict QPP? An approach based on multivariate outliers. In Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024, Proceedings, Part III. https://doi.org/10.1007/978-3-031-56063-7_38

Query performance prediction (QPP) aims to predict the success and failure of a search engine on a collection of queries and documents. State of the art predictors can enable this prediction with a degree of accuracy; however, it is far from being pe... Read More about Can we predict QPP? An approach based on multivariate outliers.

Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP (2023)
Conference Proceeding
Datta, S., Ganguly, D., Mothe, J., & Ullah, M. Z. (2023). Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP. In Proceedings of the The QPP++ 2023: Query Performance Prediction and Its Evaluation in New Tasks Workshop co-located with The 45th European Conference on Information Retrieval (ECIR) (7-12)

In information retrieval, query performance prediction aims to predict whether a search engine is likely to succeed in retrieving potentially relevant documents to a user's query. This problem is usually cast into a regression problem where a machine... Read More about Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP.

InnEO'Space PhD: Preparing Young Researchers for a successful career on Earth Observation applications (2022)
Conference Proceeding
Mothe, J., Bayer, A., Castello, V., Ciaccio, V., Del Frate, F., De Santis, D., …Voinea, M. (2022). InnEO'Space PhD: Preparing Young Researchers for a successful career on Earth Observation applications. In International Conference on Innovation in Aviation & Space to the Satisfaction of the European Citizens (11th EASN 2021) (012084). https://doi.org/10.1088/1757-899X/1226/1/012084

InnEO'Space PhD project is preparing young researchers for a successful career by developing modernised and transferable PhD courses and learning resources based on innovation skills and employers' needs as well as in-depth knowledge of high stakes a... Read More about InnEO'Space PhD: Preparing Young Researchers for a successful career on Earth Observation applications.

Defining an Optimal Configuration Set for Selective Search Strategy - A Risk-Sensitive Approach (2021)
Conference Proceeding
Mothe, J., & Ullah, M. Z. (2021). Defining an Optimal Configuration Set for Selective Search Strategy - A Risk-Sensitive Approach. In CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management (1335-1345). https://doi.org/10.1145/3459637.3482422

A search engine generally applies a single search strategy to any user query. The search combines many component processes (e.g., indexing, query expansion, search-weighting model, document ranking) and their hyperparameters, whose values are optimiz... Read More about Defining an Optimal Configuration Set for Selective Search Strategy - A Risk-Sensitive Approach.

Exploiting various word embedding models for query expansion in microblog (2020)
Conference Proceeding
Ahmed, S., Chy, A. N., & Ullah, M. Z. (2020). Exploiting various word embedding models for query expansion in microblog. In 2020 IEEE 8th R10 Humanitarian Technology Conference (R10-HTC). https://doi.org/10.1109/R10-HTC49770.2020.9357016

Microblogs, especially Twitter, make it easier to communicate with others in a real-time manner and is treated as a valuable information source. With the increasing amount of tweets, it would be fascinating to be able to extract essential information... Read More about Exploiting various word embedding models for query expansion in microblog.

An ML Model for Predicting Information Check-Worthiness using a Variety of Features (2020)
Conference Proceeding
Ullah, M. Z. (2020). An ML Model for Predicting Information Check-Worthiness using a Variety of Features. In Proceedings of the Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media (56-61)

In this communication, we introduce the important problem of information check-worthiness. We present the method we developed to automatically answer this problem. This method makes use of an elaborated information representation that combines the “i... Read More about An ML Model for Predicting Information Check-Worthiness using a Variety of Features.

Forward and backward feature selection for query performance prediction (2020)
Conference Proceeding
Déjean, S., Ionescu, R. T., Mothe, J., & Ullah, M. Z. (2020). Forward and backward feature selection for query performance prediction. In SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing (690-697). https://doi.org/10.1145/3341105.3373904

The goal of query performance prediction (QPP) is to automatically estimate the effectiveness of a search result for any given query, without relevance judgements. Post-retrieval features have been shown to be more effective for this task while being... Read More about Forward and backward feature selection for query performance prediction.

Studying the variability of system setting effectiveness by data analytics and visualization (2019)
Conference Proceeding
Déjean, S., Mothe, J., & Ullah, M. Z. (2019). Studying the variability of system setting effectiveness by data analytics and visualization. In Experimental IR Meets Multilinguality, Multimodality, and Interaction: 10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9--12, 2019, Proceedings (62-74). https://doi.org/10.1007/978-3-030-28577-7_3

Search engines differ from their modules and parameters; defining the optimal system setting is challenging the more because of the complexity of a retrieval stream. The main goal of this study is to determine which are the most important system comp... Read More about Studying the variability of system setting effectiveness by data analytics and visualization.

Information nutritional label and word embedding to estimate information check-worthiness (2019)
Conference Proceeding
Lespagnol, C., Mothe, J., & Ullah, M. Z. (2019). Information nutritional label and word embedding to estimate information check-worthiness. In SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (941-944). https://doi.org/10.1145/3331184.3331298

Automatic fact-checking is an important challenge nowadays since anyone can write about anything and spread it in social media, no matter the information quality. In this paper, we revisit the information check-worthiness problem and propose a method... Read More about Information nutritional label and word embedding to estimate information check-worthiness.

Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin (2018)
Conference Proceeding
Mizzaro, S., Mothe, J., Roitero, K., & Ullah, M. Z. (2018). Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin. In SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (1233-1236). https://doi.org/10.1145/3209978.3210146

Some methods have been developed for automatic effectiveness evaluation without relevance judgments. We propose to use those methods, and their combination based on a machine learning approach, for query performance prediction. Moreover, since predic... Read More about Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin.

Query performance prediction focused on summarized letor features (2018)
Conference Proceeding
Chifu, A., Laporte, L., Mothe, J., & Ullah, M. Z. (2018). Query performance prediction focused on summarized letor features. In SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (1177-1180). https://doi.org/10.1145/3209978.3210121

Query performance prediction (QPP) aims at automatically estimating the information retrieval system effectiveness for any user's query. Previous work has investigated several types of pre- and post-retrieval query performance predictors; the latter... Read More about Query performance prediction focused on summarized letor features.

IRIT-QFR: IRIT Query Feature Resource (2017)
Conference Proceeding
Molina, S., Mothe, J., Roques, D., Tanguy, L., & Ullah, M. Z. (2017). IRIT-QFR: IRIT Query Feature Resource. In Experimental IR Meets Multilinguality, Multimodality, and Interaction: 8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11–14, 2017, Proceedings (69-81). https://doi.org/10.1007/978-3-319-65813-1_6

In this paper, we present a resource that consists of query features associated with TREC adhoc collections. We developed two types of query features: linguistics features that can be calculated from the query itself, prior to any search although som... Read More about IRIT-QFR: IRIT Query Feature Resource.

Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification (2016)
Conference Proceeding
Ullah, M. Z., Chy, A. N., & Aono, M. (2016). Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification. In Information Retrieval Technology: 12th Asia Information Retrieval Societies Conference, AIRS 2016, Beijing, China, November 30 – December 2, 2016, Proceedings (308-314). https://doi.org/10.1007/978-3-319-48051-0_24

Understanding the users’ search intents through mining query subtopic is a challenging task and a prerequisite step for search diversification. This paper proposes mining query subtopic by exploiting the word embedding and short-text similarity measu... Read More about Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification.

Combining temporal and content aware features for microblog retrieval (2015)
Conference Proceeding
Chy, A. N., Ullah, M. Z., & Aono, M. (2015). Combining temporal and content aware features for microblog retrieval. In 2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA). https://doi.org/10.1109/ICAICTA.2015.7335353

Microblog, especially Twitter, have become an integral part of our daily life for searching latest news and events information. Due to short length characteristics of tweets, only content-relevance based search result cannot satisfy user's informatio... Read More about Combining temporal and content aware features for microblog retrieval.

Query subtopic mining for search result diversification (2014)
Conference Proceeding
Ullah, M. Z., & Aono, M. (2014). Query subtopic mining for search result diversification. In 2014 International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA) (309-314). https://doi.org/10.1109/ICAICTA.2014.7005960

Web search queries are usually short, ambiguous, and contain multiple aspects or subtopics. Different users may have different search intents (or information needs) when submitting the same query. The task of identifying the subtopics underlying a qu... Read More about Query subtopic mining for search result diversification.

Ontology based classification for multi-label image annotation (2014)
Conference Proceeding
Reshma, I. A., Ullah, M. Z., & Aono, M. (2014). Ontology based classification for multi-label image annotation. In 2014 international conference of advanced informatics: concept, theory and application (ICAICTA) (226-231). https://doi.org/10.1109/ICAICTA.2014.7005945

Image annotation has been an important task for visual information retrieval. It usually involves a multi-class multi-label classification problem. To solve this problem, many researches have been conducted during last two decades, although most of t... Read More about Ontology based classification for multi-label image annotation.

Estimating a ranked list of human hereditary diseases for clinical phenotypes by using weighted bipartite network (2013)
Conference Proceeding
Ullah, M. Z., Aono, M., & Seddiqui, M. H. (2013). Estimating a ranked list of human hereditary diseases for clinical phenotypes by using weighted bipartite network. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (3475-3478). https://doi.org/10.1109/EMBC.2013.6610290

With the availability of the huge medical knowledge data on the Internet such as the human disease network, protein-protein interaction (PPI) network, and phenotypegene, gene-disease bipartite networks, it becomes practical to help doctors by suggest... Read More about Estimating a ranked list of human hereditary diseases for clinical phenotypes by using weighted bipartite network.