SIGIR2018 Workshop on Learning From Noisy/Limited Data for IR

We are organizing the "Learning From Noisy/Limited Data for Information Retrieval" workshop which is co-located with SIGIR 2018. This is the first edition of this workshop and The goal of the workshop is to bring together researchers from industry, where data is plentiful but noisy, with researchers from academia, where data is sparse but clean, to […]

Beating the Teacher: Neural Ranking Models with Weak Supervision

Our paper "Neural Ranking Models with Weak Supervision", with Hamed Zamani, Aliaksei Severyn, Jaap Kamps, and W. Bruce Croft, has been accepted as a long paper at The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017). \o/ This paper is on the outcome of my pet project during my internship […]

ICTIR 2016 BEST PAPER AWARD

We have got the "Best paper Award" in The ACM International Conference on the Theory of Information Retrieval (ICTIR2016) for our paper "On Horizontal and Vertical Separation in Hierarchical Text Classification". \o/ Please take a look at my posts on "From Probability Ranking Principle to Strong Separation Principle", and "Two-dimensional separability in Hierarchical Text Classification") for more information on […]

Significant Words Representations of Entities

My doctoral consortium submission on "Significant Words Representations of Entities", has been accepted at the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2016). \o/ Transforming the data into a suitable representation is the first key step of data analysis, and the performance of any data-oriented method is heavily depending on it. […]

Revisiting Optimal Rank Aggregation: A Dynamic Programming Approach

Our paper "Revisiting Optimal Rank Aggregation: A Dynamic Programming Approach", withShayan A Tabrizi, Javid Dadashkarimi, Hasan Nasr Esfahani, and Azadeh Shakery, has been accepted as a short paper at the ACM SIGIR International Conference on the Theory of Information Retrieval. \o/ Rank aggregation, that is merging multiple ranked lists, is a pivotal challenge in many […]

Time-Aware Authorship Attribution for Short Text Streams

Our paper "Time-Aware Authorship Attribution for Short Text Streams", with Hosein Azarbonyad, Jaap Kamps, and Maarten Marx, has been accepted as a short paper at the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'15). \o/ Identifying authors of short texts on Internet or social media based communication systems is an […]

Entity Linking by Focusing DBpedia Candidate Entities

Entity Linking (EL) is the task of detecting mentioned entities in a text and linking them to the corresponding entries of a Knowledge Base. EL is traditionally composed of three major parts: Spotting, Candidate generation, and Candidate disambiguation. The performance of an EL system is highly dependent on the accuracy of each individual part. Regarding […]