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- research-articleJuly 2024
LADy 💃: A Benchmark Toolkit for Latent Aspect Detection Enriched with Backtranslation Augmentation
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 1172–1178https://doi.org/10.1145/3626772.3657894We present LADy ᖡ, a Python-based benchmark toolkit to facilitate extracting aspects of products or services in reviews toward which customers target their opinions and sentiments. While there has been a significant increase in aspect-based sentiment ...
- tutorialJune 2024
Collaborative Team Recommendation for Skilled Users: Objectives, Techniques, and New Perspectives
UMAP Adjunct '24: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and PersonalizationJune 2024, Pages 1–4https://doi.org/10.1145/3631700.3658521Collaborative team recommendation involves selecting users with certain skills to form a team who will, more likely than not, accomplish a complex task successfully. To automate the traditionally tedious and error-prone manual process of team formation, ...
- ArticleMarch 2024
A Streaming Approach to Neural Team Formation Training
Advances in Information RetrievalMar 2024, Pages 325–340https://doi.org/10.1007/978-3-031-56027-9_20AbstractPredicting future successful teams of experts who can effectively collaborate is challenging due to the experts’ temporality of skill sets, levels of expertise, and collaboration ties, which is overlooked by prior work. Specifically, state-of-the-...
- short-paperOctober 2023
Latent Aspect Detection via Backtranslation Augmentation
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 3943–3947https://doi.org/10.1145/3583780.3615205Within the context of review analytics, aspects are the features of products and services at which customers target their opinions and sentiments. Aspect detection helps product owners and service providers identify shortcomings and prioritize customers' ...
- short-paperOctober 2023
RePair: An Extensible Toolkit to Generate Large-Scale Datasets for Query Refinement via Transformers
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 5376–5380https://doi.org/10.1145/3583780.3615129Query refinement is the process of transforming users' queries into newrefined versions without semantic drift to enhance the relevance of search results. Prior query refiners were benchmarked on web query logs followingweak assumptions that users' input ...
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- research-articleAugust 2023
A Variational Neural Architecture for Skill-based Team Formation
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 1Article No.: 7, Pages 1–28https://doi.org/10.1145/3589762Team formation is concerned with the identification of a group of experts who have a high likelihood of effectively collaborating with each other to satisfy a collection of input skills. Solutions to this task have mainly adopted graph operations and at ...
- short-paperOctober 2022
Effective Neural Team Formation via Negative Samples
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 3908–3912https://doi.org/10.1145/3511808.3557590Forming teams of experts who collectively hold a set of required skills and can successfully cooperate is challenging due to the vast pool of feasible candidates with diverse backgrounds, skills, and personalities. Neural models have been proposed to ...
- short-paperOctober 2022
SEERa: A Framework for Community Prediction
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 4762–4766https://doi.org/10.1145/3511808.3557529Online user communities exhibit distinct temporal dynamics in response to popular topics or breaking events. Despite abundant community detection libraries, there is yet to be one that provides access to the possible user communities in future time ...
- short-paperOctober 2022
OpeNTF: A Benchmark Library for Neural Team Formation
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 3913–3917https://doi.org/10.1145/3511808.3557526We contribute OpeNTF, an open-source python-based benchmark library to support neural team formation research. Team formation falls under social information retrieval (Social IR), where the right group of experts should be retrieved to solve a task, ...
- short-paperOctober 2021
PyTFL: A Python-based Neural Team Formation Toolkit
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementOctober 2021, Pages 4716–4720https://doi.org/10.1145/3459637.3481992We present PyTFL, a library written in Python for the team formation task. In team formation task, the main objective is to form a team of experts given a set of skills. We demonstrate an efficient and well-structured open-source toolkit that can easily ...
- research-articleMay 2021
On the causal relation between real world activities and emotional expressions of social media users
- Seyed Amin Mirlohi Falavarjani,
- Jelena Jovanovic,
- Hossein Fani,
- Ali A. Ghorbani,
- Zeinab Noorian,
- Ebrahim Bagheri
Journal of the Association for Information Science and Technology (JAIST), Volume 72, Issue 6June 2021, Pages 723–743https://doi.org/10.1002/asi.24440AbstractSocial interactions through online social media have become a daily routine of many, and the number of those whose real world (offline) and online lives have become intertwined is continuously growing. As such, the interplay of individuals' online ...
- ArticleMarch 2021
An Extensible Toolkit of Query Refinement Methods and Gold Standard Dataset Generation
Advances in Information RetrievalMar 2021, Pages 498–503https://doi.org/10.1007/978-3-030-72240-1_54AbstractWe present an open-source extensible python-based toolkit that provides access to a (1) range of built-in unsupervised query expansion methods, and (2) pipeline for generating gold standard datasets for building and evaluating supervised query ...
- research-articleOctober 2020
ReQue: A Configurable Workflow and Dataset Collection for Query Refinement
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementOctober 2020, Pages 3165–3172https://doi.org/10.1145/3340531.3412775In this paper, we implement and publicly share a configurable software workflow and a collection of gold standard datasets for training and evaluating supervised query refinement methods. Existing datasets such as AOL and MS MARCO, which have been ...
- short-paperOctober 2020
Learning to Form Skill-based Teams of Experts
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementOctober 2020, Pages 2049–2052https://doi.org/10.1145/3340531.3412140We focus on the composition of teams of experts that collectively cover a set of required skills based on their historical collaboration network and expertise. Prior works are primarily based on the shortest path between experts on the expert ...
- ArticleApril 2020
Temporal Latent Space Modeling for Community Prediction
Advances in Information RetrievalApr 2020, Pages 745–759https://doi.org/10.1007/978-3-030-45439-5_49AbstractWe propose a temporal latent space model for user community prediction in social networks, whose goal is to predict future emerging user communities based on past history of users’ topics of interest. Our model assumes that each user lies within ...
- research-articleMarch 2020
User community detection via embedding of social network structure and temporal content
Information Processing and Management: an International Journal (IPRM), Volume 57, Issue 2Mar 2020https://doi.org/10.1016/j.ipm.2019.102056AbstractIdentifying and extracting user communities is an important step towards understanding social network dynamics from a macro perspective. For this reason, the work in this paper explores various aspects related to the identification of ...
- tutorialJuly 2019
Social User Interest Mining: Methods and Applications
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningJuly 2019, Pages 3235–3236https://doi.org/10.1145/3292500.3332279he abundance of user generated content on social networks pro-vides the opportunity to build models that are able to accurately and effectively extract, mine and predict users' interests with the hopes of enabling more effective user engagement, better ...
- tutorialJuly 2019
Extracting, Mining and Predicting Users' Interests from Social Networks
SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2019, Pages 1407–1408https://doi.org/10.1145/3331184.3331383The abundance of user generated content on social networks provides the opportunity to build models that are able to accurately and effectively extract, mine and predict users' interests with the hopes of enabling more effective user engagement, better ...
- short-paperOctober 2018
Predicting Personal Life Events from Streaming Social Content
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge ManagementOctober 2018, Pages 1751–1754https://doi.org/10.1145/3269206.3269313Researchers have shown that it is possible to identify reported instances of personal life events from users' social content, e.g., tweets. This is known as personal life event detection. In this paper, we take a step forward and explore the possibility ...
- short-paperOctober 2018
Causal Dependencies for Future Interest Prediction on Twitter
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge ManagementOctober 2018, Pages 1511–1514https://doi.org/10.1145/3269206.3269312The accurate prediction of users' future topics of interests on social networks can facilitate content recommendation and platform engagement. However, researchers have found that future interest prediction, especially on social networks such as Twitter,...