1 code implementation • 19 Apr 2024 • Zhaodonghui Li, Haitao Yuan, Huiming Wang, Gao Cong, Lidong Bing
In order to maintain equivalence between the rewritten query and the original one during rewriting, traditional query rewrite methods always rewrite the queries following certain rewrite rules.
no code implementations • 18 Mar 2024 • Yile Chen, Xiucheng Li, Gao Cong, Zhifeng Bao, Cheng Long
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to enhance the integration of temporal dynamics to boost the performance of various time-sensitive downstream tasks.
no code implementations • 14 Mar 2024 • Pasquale Balsebre, Weiming Huang, Gao Cong
Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks.
no code implementations • 12 Mar 2024 • Ziqi Yin, Shanshan Feng, Shang Liu, Gao Cong, Yew Soon Ong, Bin Cui
With the proliferation of spatio-textual data, Top-k KNN spatial keyword queries (TkQs), which return a list of objects based on a ranking function that evaluates both spatial and textual relevance, have found many real-life applications.
no code implementations • 6 Feb 2024 • Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang
Air quality prediction and modelling plays a pivotal role in public health and environment management, for individuals and authorities to make informed decisions.
no code implementations • 22 Dec 2023 • Tangwen Qian, Yile Chen, Gao Cong, Yongjun Xu, Fei Wang
However, the development of multi-source domain generalization in this task presents two notable issues: (1) negative transfer; (2) inadequate modeling for external factors.
1 code implementation • 21 Oct 2023 • Jiayi Xie, Shang Liu, Gao Cong, Zhenzhong Chen
In this work, we propose a Unified framework of Sequential Search and Recommendation (UnifiedSSR) for joint learning of user behavior history in both search and recommendation scenarios.
3 code implementations • 9 Oct 2023 • Zezhi Shao, Fei Wang, Yongjun Xu, Wei Wei, Chengqing Yu, Zhao Zhang, Di Yao, Guangyin Jin, Xin Cao, Gao Cong, Christian S. Jensen, Xueqi Cheng
Moreover, based on the proposed BasicTS and rich heterogeneous MTS datasets, we conduct an exhaustive and reproducible performance and efficiency comparison of popular models, providing insights for researchers in selecting and designing MTS forecasting models.
no code implementations • 1 Oct 2023 • Pasquale Balsebre, Weiming Huang, Gao Cong, Yi Li
This can be attributed to the intrinsic heterogeneity of geospatial data, which encompasses different data types, including points, segments and regions, as well as multiple information modalities, such as a spatial position, visual characteristics and textual annotations.
no code implementations • 13 Apr 2023 • Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao
In this work, we explore the promises and challenges of developing multimodal foundation models for GeoAI.
no code implementations • 28 Feb 2023 • Yufan Sheng, Xin Cao, Yixiang Fang, Kaiqi Zhao, Jianzhong Qi, Gao Cong, Wenjie Zhang
In this paper, we propose WISK, a learned index for spatial keyword queries, which self-adapts for optimizing querying costs given a query workload.
no code implementations • 25 Jan 2023 • Daniel Rugeles, Zhen Hai, Juan Felipe Carmona, Manoranjan Dash, Gao Cong
In text mining, topic models are a type of probabilistic generative models for inferring latent semantic topics from text corpus.
1 code implementation • 15 Nov 2022 • Liang Zhang, Cheng Long, Gao Cong
Motivated by the success of contrastive learning for representation learning, we propose to leverage it for multi-view region representation learning and design a model called ReMVC (Region Embedding with Multi-View Contrastive Learning) by following two guidelines: i) comparing a region with others within each view for effective representation extraction and ii) comparing a region with itself across different views for cross-view information sharing.
1 code implementation • 12 Nov 2022 • Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi
Detecting anomalous trajectories has become an important task in many location-based applications.
no code implementations • 14 Oct 2022 • Tiantian He, Haicang Zhou, Yew-Soon Ong, Gao Cong
We further propose Graph selective attention networks (SATs) to learn representations from the highly correlated node features identified and investigated by different SA mechanisms.
1 code implementation • SIGMOD/PODS 2022 • Dezhong Yao, Yuhong Gu, Gao Cong, Hai Jin, Xinqiao Lv
However, there is often interdependence between different pairs of ER decisions, e. g., the entities from the same data source are usually semantically related to each other.
Ranked #1 on Entity Resolution on WDC Watches-small
no code implementations • 28 Feb 2022 • Yile Chen, Xiucheng Li, Gao Cong, Cheng Long, Zhifeng Bao, Shang Liu, Wanli Gu, Fuzheng Zhang
As a fundamental component in location-based services, inferring the relationship between points-of-interests (POIs) is very critical for service providers to offer good user experience to business owners and customers.
1 code implementation • 13 Sep 2021 • Yuxing Han, Ziniu Wu, Peizhi Wu, Rong Zhu, Jingyi Yang, Liang Wei Tan, Kai Zeng, Gao Cong, Yanzhao Qin, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Jiangneng Li, Bin Cui
Therefore, we propose a new metric P-Error to evaluate the performance of CardEst methods, which overcomes the limitation of Q-Error and is able to reflect the overall end-to-end performance of CardEst methods.
2 code implementations • 9 Jun 2021 • Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu
In GCE-GNN, we propose a novel global-level item representation learning layer, which employs a session-aware attention mechanism to recursively incorporate the neighbors' embeddings of each node on the global graph.
no code implementations • 8 Mar 2021 • Tu Gu, Kaiyu Feng, Gao Cong, Cheng Long, Zheng Wang, Sheng Wang
Learned indices have been proposed to replace classic index structures like B-Tree with machine learning (ML) models.
no code implementations • 20 Nov 2020 • Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu, Shanshan Feng
Based on BGNN, we propose a novel approach, called Session-based Recommendation with Global Information (SRGI), which infers the user preferences via fully exploring global item-transitions over all sessions from two different perspectives: (i) Fusion-based Model (SRGI-FM), which recursively incorporates the neighbor embeddings of each node on global graph into the learning process of session level item representation; and (ii) Constrained-based Model (SRGI-CM), which treats the global-level item-transition information as a constraint to ensure the learned item embeddings are consistent with the global item-transition.
no code implementations • 5 Mar 2020 • Zheng Wang, Cheng Long, Gao Cong, Yiding Liu
Similar trajectory search is a fundamental problem and has been well studied over the past two decades.
no code implementations • 28 Feb 2019 • Ce Ju, Zheng Wang, Cheng Long, Xiao-Yu Zhang, Gao Cong, Dong Eui Chang
Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.)
Robotics I.2.9; I.2.0
no code implementations • 17 Dec 2018 • Zheng Wang, Ce Ju, Gao Cong, Cheng Long
Recently, the topic of graph representation learning has received plenty of attention.
no code implementations • 5 Sep 2018 • Lucas Vinh Tran, Yi Tay, Shuai Zhang, Gao Cong, Xiao-Li Li
This paper investigates the notion of learning user and item representations in non-Euclidean space.
Ranked #1 on Recommendation Systems on MovieLens 20M (HR@10 metric)
no code implementations • 12 Apr 2018 • Lucas Vinh Tran, Tuan-Anh Nguyen Pham, Yi Tay, Yiding Liu, Gao Cong, Xiao-Li Li
Our proposed approach hinges upon the key intuition that the decision making process (in groups) is generally dynamic, i. e., a user's decision is highly dependent on the other group members.
1 code implementation • 19 Feb 2018 • Daniel Rugeles, Zhen Hai, Gao Cong, Manoranjan Dash
Bayesian graphical models have been shown to be a powerful tool for discovering uncertainty and causal structure from real-world data in many application fields.
no code implementations • EMNLP 2017 • Zhuoxuan Jiang, Shanshan Feng, Gao Cong, Chunyan Miao, Xiaoming Li
Recent years have witnessed the proliferation of Massive Open Online Courses (MOOCs).
1 code implementation • 1 Aug 2015 • Xutao Li, Gao Cong, Xiaoli Li, Tuan Anh Nguyen Pham, Shonali Priyadarsini Krishnaswamy
In this paper, we propose a ranking based geographical factorization method, called Rank-GeoFM, for POI recommendation, which addresses the two challenges.
no code implementations • 1 Nov 2014 • Quan Yuan, Gao Cong, Aixin Sun
In this paper, we focus on the problem of time-aware POI recommendation, which aims at recommending a list of POIs for a user to visit at a given time.
no code implementations • 2011 2011 • Xin Cao1, Gao Cong
We define the problem of retrieving a group of spatial web objects such that the group’s keywords cover the query’s keywords and such that objects are nearest to the query location and have the lowest inter-object distances.