202 citations · 502 across the 21 of their papers we have counts for
25 papers
GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval
Iain Mackie, Ivan Sekulic, Shubham Chatterjee +2
Recent studies show that Generative Relevance Feedback (GRF), using text generated by Large Language Models (LLMs), can enhance the effectiveness of query expansion. However, LLMs…
Exploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond
Paul Owoicho, Ivan Sekulić, Mohammad Aliannejadi +2
This research aims to explore various methods for assessing user feedback in mixed-initiative conversational search (CS) systems. While CS systems enjoy profuse advancements across…
Evaluating Mixed-initiative Conversational Search Systems via User Simulation
Ivan Sekulić, Mohammad Aliannejadi, Fabio Crestani
Clarifying the underlying user information need by asking clarifying questions is an important feature of modern conversational search system. However, evaluation of such systems t…
Mental Disorders on Online Social Media Through the Lens of Language and Behaviour: Analysis and Visualisation
Esteban A. Ríssola, Mohammad Aliannejadi, Fabio Crestani
Due to the worldwide accessibility to the Internet along with the continuous advances in mobile technologies, physical and digital worlds have become completely blended, and the pr…
A Systematic Analysis on the Impact of Contextual Information on Point-of-Interest Recommendation
Hossein A. Rahmani, Mohammad Aliannejadi, Mitra Baratchi +1
As the popularity of Location-based Social Networks (LBSNs) increases, designing accurate models for Point-of-Interest (POI) recommendation receives more attention. POI recommendat…
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…
User Engagement Prediction for Clarification in Search
Ivan Sekulić, Mohammad Aliannejadi, Fabio Crestani
Clarification is increasingly becoming a vital factor in various topics of information retrieval, such as conversational search and modern Web search engines. Prompting the user fo…
Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani +1
Users install many apps on their smartphones, raising issues related to information overload for users and resource management for devices. Moreover, the recent increase in the use…
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…
A Tool for Conducting User Studies on Mobile Devices
Luca Costa, Mohammad Aliannejadi, Fabio Crestani
With the ever-growing interest in the area of mobile information retrieval and the ongoing fast development of mobile devices and, as a consequence, mobile apps, an active research…
Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval
Mohammad Aliannejadi, Manajit Chakraborty, Esteban Andrés Ríssola +1
With the improvements in speech recognition and voice generation technologies over the last years, a lot of companies have sought to develop conversation understanding systems that…
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…
A Joint Two-Phase Time-Sensitive Regularized Collaborative Ranking Model for Point of Interest Recommendation
Mohammad Aliannejadi, Dimitrios Rafailidis, Fabio Crestani
The popularity of location-based social networks (LBSNs) has led to a tremendous amount of user check-in data. Recommending points of interest (POIs) plays a key role in satisfying…
LGLMF: Local Geographical based Logistic Matrix Factorization Model for POI Recommendation
Hossein A. Rahmani, Mohammad Aliannejadi, Sajad Ahmadian +3
With the rapid growth of Location-Based Social Networks, personalized Points of Interest (POIs) recommendation has become a critical task to help users explore their surroundings.…
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,…
Asking Clarifying Questions in Open-Domain Information-Seeking Conversations
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani +1
Users often fail to formulate their complex information needs in a single query. As a consequence, they may need to scan multiple result pages or reformulate their queries, which m…
Mobile Information Retrieval
Fabio Crestani, Stefano Mizzaro, Ivan Scagnetto
Mobile Information Retrieval (Mobile IR) is a relatively recent branch of Information Retrieval (IR) that is concerned with enabling users to carry out, using a mobile device, all…
Understanding Mobile Search Task Relevance and User Behaviour in Context
Mohammad Aliannejadi, Morgan Harvey, Luca Costa +2
Improvements in mobile technologies have led to a dramatic change in how and when people access and use information, and is having a profound impact on how users address their dail…
A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion
Mohammad Aliannejadi, Dimitrios Rafailidis, Fabio Crestani
Recommending venues plays a critical rule in satisfying users' needs on location-based social networks. Recent studies have explored the idea of adopting collaborative ranking (CR)…
Personalized Context-Aware Point of Interest Recommendation
Mohammad Aliannejadi, Fabio Crestani
Personalized recommendation of Points of Interest (POIs) plays a key role in satisfying users on Location-Based Social Networks (LBSNs). In this paper, we propose a probabilistic m…
Target Apps Selection: Towards a Unified Search Framework for Mobile Devices
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani +1
With the recent growth of conversational systems and intelligent assistants such as Apple Siri and Google Assistant, mobile devices are becoming even more pervasive in our lives. A…
Venue Suggestion Using Social-Centric Scores
Mohammad Aliannejadi, Fabio Crestani
User modeling is a very important task for making relevant suggestions of venues to the users. These suggestions are often based on matching the venues' features with the users' pr…
Comparative Opinion Mining: A Review
Kasturi Dewi Varathan, Anastasia Giachanou, Fabio Crestani
Opinion mining refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in textual material. Opi…