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Learning from data streams is among the most vital fields of contemporary data mining. The online analysis of information coming from those potentially unbounded data sources allows for designing reactive up-to-date models capable of…

Machine Learning · Computer Science 2020-10-16 Łukasz Korycki , Bartosz Krawczyk

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of…

Robotics · Computer Science 2020-07-27 Andrey Rudenko , Luigi Palmieri , Michael Herman , Kris M. Kitani , Dariu M. Gavrila , Kai O. Arras

In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task depending on many external factors. The topology of the scene and the interactions between the pedestrians are just some of them. Due to…

Machine Learning · Computer Science 2022-09-12 Raphael Korbmacher , Antoine Tordeux

Workers spend a significant amount of time learning how to make good decisions. Evaluating the efficacy of a given decision, however, can be complicated -- e.g., decision outcomes are often long-term and relate to the original decision in…

Machine Learning · Computer Science 2024-03-20 Hamsa Bastani , Osbert Bastani , Wichinpong Park Sinchaisri

With the growth of using cell phones and the increase in diversity of smart mobile devices, a massive volume of data is generated continuously in the process of using these devices. Among these data, Call Detail Records, CDR, is highly…

Machine Learning · Computer Science 2019-12-24 Mohammad Saleh Mahdizadeh , Behnam Bahrak

Decision-making, motion planning, and trajectory prediction are crucial in autonomous driving systems. By accurately forecasting the movements of other road users, the decision-making capabilities of the autonomous system can be enhanced,…

Robotics · Computer Science 2024-09-17 Mais Jamal , Aleksandr Panov

Click-through rate prediction plays an important role in the field of recommender system and many other applications. Existing methods mainly extract user interests from user historical behaviors. However, behavioral sequences only contain…

Information Retrieval · Computer Science 2021-09-28 Yunfei Chu , Xiaofu Chang , Kunyang Jia , Jingzhen Zhou , Hongxia Yang

Modern web-based platforms show ranked lists of recommendations to users, attempting to maximise user satisfaction or business metrics. Typically, the goal of such systems boils down to maximising the exposure probability for items that are…

Information Retrieval · Computer Science 2023-07-27 Olivier Jeunen

Web usage mining: automatic discovery of patterns in clickstreams and associated data collected or generated as a result of user interactions with one or more Web sites. This paper describes web usage mining for our college log files to…

Databases · Computer Science 2013-10-10 Dhanamma Jagli , Sangeeta Oswal

Given real-time sensor data streams obtained from machines, how can we continuously predict when a machine failure will occur? This work aims to continuously forecast the timing of future events by analyzing multi-sensor data streams. A key…

Machine Learning · Computer Science 2026-01-16 Kota Nakamura , Koki Kawabata , Yasuko Matsubara , Yasushi Sakurai

Sequential recommendation requires the recommender to capture the evolving behavior characteristics from logged user behavior data for accurate recommendations. However, user behavior sequences are viewed as a script with multiple ongoing…

Information Retrieval · Computer Science 2022-06-15 Zhiyu Yao , Xinyang Chen , Sinan Wang , Qinyan Dai , Yumeng Li , Tanchao Zhu , Mingsheng Long

One particularly promising use case of Large Language Models (LLMs) for recommendation is the automatic generation of Natural Language (NL) user taste profiles from consumption data. These profiles offer interpretable and editable…

Information Retrieval · Computer Science 2025-07-23 Bruno Sguerra , Elena V. Epure , Harin Lee , Manuel Moussallam

The future motion of traffic participants is inherently uncertain. To plan safely, therefore, an autonomous agent must take into account multiple possible trajectory outcomes and prioritize them. Recently, this problem has been addressed…

Computer Vision and Pattern Recognition · Computer Science 2021-08-02 Christoph Schöller , Alois Knoll

Large quantifies of online user activity data, such as weekly web search volumes, which co-evolve with the mutual influence of several queries and locations, serve as an important social sensor. It is an important task to accurately…

Social and Information Networks · Computer Science 2022-09-20 Taichi Murayama , Yasuko Matsubara , Yasushi Sakurai

Human trajectory forecasting is a critical challenge in fields such as robotics and autonomous driving. Due to the inherent uncertainty of human actions and intentions in real-world scenarios, various unexpected occurrences may arise. To…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Yuxin Yang , Pengfei Zhu , Mengshi Qi , Huadong Ma

When driving, people make decisions based on current traffic as well as their desired route. They have a mental map of known routes and are often able to navigate without needing directions. Current self-driving models improve their…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Iulia Paraicu , Marius Leordeanu

The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. A collaborative filtering (CF) algorithm recommends items of interest to the target user by leveraging the votes given…

Information Retrieval · Computer Science 2018-05-09 Xu He , Bin Liu , Ke-Jia Chen

Forecasting human trajectories in complex dynamic environments plays a critical role in autonomous vehicles and intelligent robots. Most existing methods learn to predict future trajectories by behavior clues from history trajectories and…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Guangyi Chen , Junlong Li , Jiwen Lu , Jie Zhou

When a developer is writing code they are usually focused and in a state-of-mind which some refer to as flow. Breaking out of this flow can cause the developer to lose their train of thought and have to start their thought process from the…

Software Engineering · Computer Science 2020-10-13 Tyson Bulmer , Lloyd Montgomery , Daniela Damian

In the nascent days of e-content delivery, having a superior product was enough to give companies an edge against the competition. With today's fiercely competitive market, one needs to be multiple steps ahead, especially when it comes to…

Machine Learning · Computer Science 2014-05-21 Everaldo Aguiar , Saurabh Nagrecha , Nitesh V. Chawla