202 citations · 626 across the 29 of their papers we have counts for
34 papers
Zero-Shot and Efficient Clarification Need Prediction in Conversational Search
Lili Lu, Chuan Meng, Federico Ravenda +2
Clarification need prediction (CNP) is a key task in conversational search, aiming to predict whether to ask a clarifying question or give an answer to the current user query. Howe…
Interactions with Generative Information Retrieval Systems
Mohammad Aliannejadi, Jacek Gwizdka, Hamed Zamani
At its core, information access and seeking is an interactive process. In existing search engines, interactions are limited to a few pre-defined actions, such as "requery", "click…
Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions
Zahra Abbasiantaeb, Yifei Yuan, Evangelos Kanoulas +1
Conversational question-answering (CQA) systems aim to create interactive search systems that effectively retrieve information by interacting with users. To replicate human-to-huma…
Query Performance Prediction: From Ad-hoc to Conversational Search
Chuan Meng, Negar Arabzadeh, Mohammad Aliannejadi +1
Query performance prediction (QPP) is a core task in information retrieval. The QPP task is to predict the retrieval quality of a search system for a query without relevance judgme…
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…
IGLU 2022: Interactive Grounded Language Understanding in a Collaborative Environment at NeurIPS 2022
Julia Kiseleva, Alexey Skrynnik, Artem Zholus +14
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…
Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +18
Human intelligence has the remarkable ability to quickly adapt to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new t…
Understanding User Satisfaction with Task-oriented Dialogue Systems
Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke
Dialogue systems are evaluated depending on their type and purpose. Two categories are often distinguished: (1) task-oriented dialogue systems (TDS), which are typically evaluat…
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…
Towards Building Economic Models of Conversational Search
Leif Azzopardi, Mohammad Aliannejadi, Evangelos Kanoulas
Various conceptual and descriptive models of conversational search have been proposed in the literature -- while useful, they do not provide insights into how interaction between t…
Analysing Mixed Initiatives and Search Strategies during Conversational Search
Mohammad Aliannejadi, Leif Azzopardi, Hamed Zamani +3
Information seeking conversations between users and Conversational Search Agents (CSAs) consist of multiple turns of interaction. While users initiate a search session, ideally a C…
Cross-Market Product Recommendation
Hamed Bonab, Mohammad Aliannejadi, Ali Vardasbi +2
We study the problem of recommending relevant products to users in relatively resource-scarce markets by leveraging data from similar, richer in resource auxiliary markets. We hypo…
Ranking Clarifying Questions Based on Predicted User Engagement
Tom Lotze, Stefan Klut, Mohammad Aliannejadi +1
To improve online search results, clarification questions can be used to elucidate the information need of the user. This research aims to predict the user engagement with the clar…
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…
MICROS: Mixed-Initiative ConveRsatiOnal Systems Workshop
Ida Mele, Cristina Ioana Muntean, Mohammad Aliannejadi +1
The 1st edition of the workshop on Mixed-Initiative ConveRsatiOnal Systems (MICROS@ECIR2021) aims at investigating and collecting novel ideas and contributions in the field of conv…
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…
A Canine Census to Influence Public Policy
Matias Apa, Maria Cecilia Faini, Mohammad Aliannejadi +1
The potential threat that domestic animals pose to the health of human populations tends to be overlooked. We posit that positive steps forward can be made in this area, via suitab…
On Estimating the Training Cost of Conversational Recommendation Systems
Stefanos Antaris, Dimitrios Rafailidis, Mohammad Aliannejadi
Conversational recommendation systems have recently gain a lot of attention, as users can continuously interact with the system over multiple conversational turns. However, convers…
ConvAI3: Generating Clarifying Questions for Open-Domain Dialogue Systems (ClariQ)
Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin +2
This document presents a detailed description of the challenge on clarifying questions for dialogue systems (ClariQ). The challenge is organized as part of the Conversational AI ch…
Analysing the Effect of Clarifying Questions on Document Ranking in Conversational Search
Antonios Minas Krasakis, Mohammad Aliannejadi, Nikos Voskarides +1
Recent research on conversational search highlights the importance of mixed-initiative in conversations. To enable mixed-initiative, the system should be able to ask clarifying que…
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…
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…