28 citations · 57 across the 12 of their papers we have counts for
12 papers
Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement
Maryam Mousavian, Zahra Abbasiantaeb, Mohammad Aliannejadi +1
The presence of social biases in Natural Language Processing (NLP) and Information Retrieval (IR) systems is an ongoing challenge, which underlines the importance of developing rob…
Clarifying the Path to User Satisfaction: An Investigation into Clarification Usefulness
Hossein A. Rahmani, Xi Wang, Mohammad Aliannejadi +2
Clarifying questions are an integral component of modern information retrieval systems, directly impacting user satisfaction and overall system performance. Poorly formulated quest…
Analyzing Coherency in Facet-based Clarification Prompt Generation for Search
Oleg Litvinov, Ivan Sekulić, Mohammad Aliannejadi +1
Clarifying user's information needs is an essential component of modern search systems. While most of the approaches for constructing clarifying prompts rely on query facets, the i…
Experiments on Generalizability of BERTopic on Multi-Domain Short Text
Muriël de Groot, Mohammad Aliannejadi, Marcel R. Haas
Topic modeling is widely used for analytically evaluating large collections of textual data. One of the most popular topic techniques is Latent Dirichlet Allocation (LDA), which is…
Towards Confidence-aware Calibrated Recommendation
Mohammadmehdi Naghiaei, Hossein A. Rahmani, Mohammad Aliannejadi +1
Recommender systems utilize users' historical data to learn and predict their future interests, providing them with suggestions tailored to their tastes. Calibration ensures that t…
Experiments on Generalizability of User-Oriented Fairness in Recommender Systems
Hossein A. Rahmani, Mohammadmehdi Naghiaei, Mahdi Dehghan +1
Recent work in recommender systems mainly focuses on fairness in recommendations as an important aspect of measuring recommendations quality. A fairness-aware recommender system ai…
Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation
Kosar Seyedhoseinzadeh, Hossein A. Rahmani, Mohsen Afsharchi +1
Recommender Systems (RSs) aim to model and predict the user preference while interacting with items, such as Points of Interest (POIs). These systems face several challenges, such…
Keyword Extraction for Improved Document Retrieval in Conversational Search
Oleg Borisov, Mohammad Aliannejadi, Fabio Crestani
Recent research has shown that mixed-initiative conversational search, based on the interaction between users and computers to clarify and improve a query, provides enormous advant…
The Impact of User Demographics and Task Types on Cross-App Mobile Search
Mohammad Aliannejadi, Fabio Crestani, Theo Huibers +3
Recent developments in the mobile app industry have resulted in various types of mobile apps, each targeting a different need and a specific audience. Consequently, users access di…
Longformer for MS MARCO Document Re-ranking Task
Ivan Sekulić, Amir Soleimani, Mohammad Aliannejadi +1
Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard. The best perfo…
Joint Geographical and Temporal Modeling based on Matrix Factorization for Point-of-Interest Recommendation
Hossein A. Rahmani, Mohammad Aliannejadi, Mitra Baratchi +1
With the popularity of Location-based Social Networks, Point-of-Interest (POI) recommendation has become an important task, which learns the users' preferences and mobility pattern…
Category-Aware Location Embedding for Point-of-Interest Recommendation
Hossein A. Rahmani, Mohammad Aliannejadi, Rasoul Mirzaei Zadeh +3
Recently, Point of interest (POI) recommendation has gained ever-increasing importance in various Location-Based Social Networks (LBSNs). With the recent advances of neural models,…