Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Linhong Zhu"'
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 11:1-26
Real-world networks are often organized as modules or communities of similar nodes that serve as functional units. These networks are also rich in content, with nodes having distinguishing features or attributes. In order to discover a network's modu
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 28:2765-2777
We propose a temporal latent space model for link prediction in dynamic social networks, where the goal is to predict links over time based on a sequence of previous graph snapshots. The model assumes that each user lies in an unobserved latent space
Publikováno v:
GeoInformatica. 20:529-568
With the progress of mobile devices and wireless broadband, a new eMarket platform, termed spatial crowdsourcing is emerging, which enables workers (aka crowd) to perform a set of spatial tasks (i.e., tasks related to a geographical location and time
Publikováno v:
ICDM
Due to the recent vast availability of transportation traffic data, major research efforts have been devoted to traffic prediction, which is useful in many applications such as urban planning, traffic management and navigations systems. Current predi
Publikováno v:
ICDE
Understanding and characterizing the processes driving social interactions is one of the fundamental problems in social network research. A particular instance of this problem, known as link prediction, has recently attracted considerable attention i
In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption. Homophily label propagation (i.e., two connected nodes share similar labels) in homogeneous graph (with same types of vertices and rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75478a52b02034c6ed3d5a6c4b25aede
Publikováno v:
KDD
Real-time traffic prediction from high-fidelity spatiotemporal traffic sensor datasets is an important problem for intelligent transportation systems and sustainability. However, it is challenging due to the complex topological dependencies and high
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7c1c695465a085de959a9db0a1fd19c
http://arxiv.org/abs/1602.04301
http://arxiv.org/abs/1602.04301
We present our solution to the job recommendation task for RecSys Challenge 2016. The main contribution of our work is to combine temporal learning with sequence modeling to capture complex user-item activity patterns to improve job recommendations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72eefa65cb74d1a024896901e7d9092f
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319465227
International Semantic Web Conference (1)
International Semantic Web Conference (1)
Entity resolution is the task of identifying all mentions that represent the same real-world entity within a knowledge base or across multiple knowledge bases. We address the problem of performing entity resolution on RDF graphs containing multiple t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68b82c867c2618b3fc9c43bf81637114
https://doi.org/10.1007/978-3-319-46523-4_39
https://doi.org/10.1007/978-3-319-46523-4_39
Publikováno v:
SIGSPATIAL/GIS
A new platform, termed spatial crowdsourcing, is emerging which enables a requester to commission workers to physically travel to some specified locations to perform a set of spatial tasks (i.e., tasks related to a geographical location and time). Th