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- demonstrationNovember 2022
Active learning for transformer models in direction query tagging
SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information SystemsArticle No.: 70, Pages 1–4https://doi.org/10.1145/3557915.3561006Correct understanding of direction queries is essential in map search for providing accurate direction related results, including routing, travel distance, travel time estimation, etc. Slot tagging is the process of recognizing and annotating query terms ...
- research-articleOctober 2022
Action2Score: An Embedding Approach to Score Player Action
Proceedings of the ACM on Human-Computer Interaction (PACMHCI), Volume 6, Issue CHI PLAYArticle No.: 220, Pages 1–23https://doi.org/10.1145/3549483Multiplayer Online Battle Arena (MOBA) is one of the most successful game genres. MOBA games such as League of Legends have competitive environments where players race for their rank. In most MOBA games, a player's rank is determined by the match result (...
- research-articleOctober 2022
OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification
MM '22: Proceedings of the 30th ACM International Conference on MultimediaPages 6269–6277https://doi.org/10.1145/3503161.3547839Scene segmentation and classification (SSC) serve as a critical step towards the field of video structuring analysis. Intuitively, jointly learning of these two tasks can promote each other by sharing common information. However, scene segmentation ...
- research-articleOctober 2020
GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementPages 435–443https://doi.org/10.1145/3340531.3411981With the recent advancement of deep learning, molecular representation learning -- automating the discovery of feature representation of molecular structure, has attracted significant attention from both chemists and machine learning researchers. Deep ...
- research-articleSeptember 2020
A window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensor
- Yiwen Dong,
- Jingxiao Liu,
- Yitao Gao,
- Sulagna Sarkar,
- Zhizhang Hu,
- Jonathon Fagert,
- Shijia Pan,
- Pei Zhang,
- Hae Young Noh,
- Mostafa Mirshekari
UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable ComputersPages 390–395https://doi.org/10.1145/3410530.3414336This paper introduces a window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensors. Nurse care activity recognition is an essential part of ensuring high quality patient care ...
- research-articleAugust 2020
Disentangled Self-Supervision in Sequential Recommenders
KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningPages 483–491https://doi.org/10.1145/3394486.3403091To learn a sequential recommender, the existing methods typically adopt the sequence-to-item (seq2item) training strategy, which supervises a sequence model with a user's next behavior as the label and the user's past behaviors as the input. The ...
- research-articleJanuary 2020
Topic enhanced word embedding for toxic content detection in Q&A sites
ASONAM '19: Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningPages 1064–1071https://doi.org/10.1145/3341161.3345332Increasingly, users are adopting community question-and-answer (Q&A) sites to exchange information. Detecting and eliminating toxic and divisive content in these Q&A sites are paramount tasks to ensure a safe and constructive environment for the users. ...
- research-articleJuly 2019
HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningPages 783–792https://doi.org/10.1145/3292500.3330876In many complex domains, the input data are often not suited for the typical vector representations used in deep learning models. For example, in relational learning and computer vision tasks, the data are often better represented as sets (e.g., the ...
- ArticleMarch 2007
Condensative stream query language for data streams
In contrast to traditional database queries, a query on stream data is continuous in that it is periodically evaluated over fractions (sliding windows) of the data stream. This introduces challenges beyond those encountered when processing traditional ...
