1 code implementation • 4 Mar 2024 • Ivan Sekulić, Krisztian Balog, Fabio Crestani
One approach expands answers with inline definitions of salient entities, making the answer self-contained.
no code implementations • 21 Jan 2024 • Ivan Sekulić, Weronika Łajewska, Krisztian Balog, Fabio Crestani
While the body of research directed towards constructing and generating clarifying questions in mixed-initiative conversational search systems is vast, research aimed at processing and comprehending users' answers to such questions is scarce.
no code implementations • 9 Jan 2024 • Oleg Litvinov, Ivan Sekulić, Mohammad Aliannejadi, Fabio Crestani
Clarifying user's information needs is an essential component of modern search systems.
no code implementations • 16 Jun 2023 • Iain Mackie, Ivan Sekulic, Shubham Chatterjee, Jeffrey Dalton, Fabio Crestani
Recent studies show that Generative Relevance Feedback (GRF), using text generated by Large Language Models (LLMs), can enhance the effectiveness of query expansion.
1 code implementation • 26 Apr 2023 • Paul Owoicho, Ivan Sekulić, Mohammad Aliannejadi, Jeffrey Dalton, Fabio Crestani
To this end, we propose a user simulator-based framework for multi-turn interactions with a variety of mixed-initiative CS systems.
1 code implementation • 17 Apr 2022 • 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.
no code implementations • 7 Feb 2022 • Esteban A. Ríssola, Mohammad Aliannejadi, Fabio Crestani
As for emotional expression, we observe that affected users tend to share emotions more regularly than control individuals on average.
no code implementations • 20 Jan 2022 • Hossein A. Rahmani, Mohammad Aliannejadi, Mitra Baratchi, Fabio Crestani
The major contributions of this paper are: (i) providing an extensive survey of context-aware location recommendation (ii) quantifying and analyzing the impact of different contextual information (e. g., social, temporal, spatial, and categorical) in the POI recommendation on available baselines and two new linear and non-linear models, that can incorporate all the major contextual information into a single recommendation model, and (iii) evaluating the considered models using two well-known real-world datasets.
no code implementations • 14 Sep 2021 • Mohammad Aliannejadi, Fabio Crestani, Theo Huibers, Monica Landoni, Emiliana Murgia, Maria Soledad Pera
Recent developments in the mobile app industry have resulted in various types of mobile apps, each targeting a different need and a specific audience.
no code implementations • 13 Sep 2021 • 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 advantages.
1 code implementation • 8 Feb 2021 • Ivan Sekulić, Mohammad Aliannejadi, Fabio Crestani
Prompting the user for clarification in a search session can be very beneficial to the system as the user's explicit feedback helps the system improve retrieval massively.
1 code implementation • 9 Jan 2021 • Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani, W. Bruce Croft
Here we focus on context-aware models to leverage the rich contextual information available to mobile devices.
1 code implementation • 20 Sep 2020 • Ivan Sekulić, Amir Soleimani, Mohammad Aliannejadi, Fabio Crestani
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.
1 code implementation • 31 Jan 2020 • 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 area lies in studying users' behavior and search queries users submit on mobile devices.
1 code implementation • 24 Jan 2020 • Hossein A. Rahmani, Mohammad Aliannejadi, Mitra Baratchi, Fabio Crestani
Previous studies show that incorporating contextual information such as geographical and temporal influences is necessary to improve POI recommendation by addressing the data sparsity problem.
1 code implementation • 22 Dec 2019 • Mohammad Aliannejadi, Manajit Chakraborty, Esteban Andrés Ríssola, Fabio Crestani
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 run on mobile phones or smart home devices through natural language interfaces.
no code implementations • 16 Sep 2019 • Mohammad Aliannejadi, Dimitrios Rafailidis, Fabio Crestani
In this article, we propose a two-phase CR algorithm that incorporates the geographical influence of POIs and is regularized based on the variance of POIs popularity and users' activities over time.
1 code implementation • 14 Sep 2019 • Hossein A. Rahmani, Mohammad Aliannejadi, Sajad Ahmadian, Mitra Baratchi, Mohsen Afsharchi, Fabio Crestani
To address these problems, a POI recommendation method is proposed in this paper based on a Local Geographical Model, which considers both users' and locations' points of view.
no code implementations • 31 Jul 2019 • Hossein A. Rahmani, Mohammad Aliannejadi, Rasoul Mirzaei Zadeh, Mitra Baratchi, Mohsen Afsharchi, Fabio Crestani
With the recent advances of neural models, much work has sought to leverage neural networks to learn neural embeddings in a pre-training phase that achieve an improved representation of POIs and consequently a better recommendation.
2 code implementations • 15 Jul 2019 • Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani, W. Bruce Croft
In this paper, we formulate the task of asking clarifying questions in open-domain information-seeking conversational systems.
no code implementations • WS 2019 • Esteban R{\'\i}ssola, Diana Ram{\'\i}rez-Cifuentes, Ana Freire, Fabio Crestani
This paper describes the participation of the USI-UPF team at the shared task of the 2019 Computational Linguistics and Clinical Psychology Workshop (CLPsych2019).
no code implementations • WS 2018 • Esteban R{\'\i}ssola, Anastasia Giachanou, Fabio Crestani
This paper describes the participation of USI-IR in WASSA 2018 Implicit Emotion Shared Task.
no code implementations • 22 Mar 2018 • Mohammad Aliannejadi, Fabio Crestani
These scores model each user by focusing on the different types of information extracted from venues that they have previously visited.
no code implementations • 24 Dec 2017 • Kasturi Dewi Varathan, Anastasia Giachanou, Fabio Crestani
Opinion mining, also known as sentiment analysis, has received a lot of attention in recent times, as it provides a number of tools to analyse the public opinion on a number of different topics.