Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Junhao Gan"'
Publikováno v:
The VLDB Journal. 29:1475-1500
Learning users’ preferences is critical to personalized search and recommendation. Most such systems depend on lists of items rank-ordered according to the user’s preference. Ideally, we want the system to adjust its estimate of users’ preferen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ac6ba97f596e7dfa513f8b6a7997bb8
https://doi.org/10.1007/s00778-020-00623-8
https://doi.org/10.1007/s00778-020-00623-8
Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions. However, the cost of examining all the possible higher-order feature interactions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efbd24254765bb7d04e9a343eb69ab27
Publikováno v:
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval.
User and item attributes are essential side-information; their interactions (i.e., their co-occurrence in the sample data) can significantly enhance prediction accuracy in various recommender systems. We identify two different types of attribute inte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9ef226f905fada1584c823d365e691d
https://doi.org/10.1145/3404835.3462833
https://doi.org/10.1145/3404835.3462833
Publikováno v:
SIGMOD Conference
Structural Clustering ($DynClu$) is one of the most popular graph clustering paradigms. In this paper, we consider $StrClu$ under two commonly adapted similarities, namely Jaccard similarity and cosine similarity on a dynamic graph, $G = \langle V, E
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90c6f11d69f53ee297829133b898e98c
https://doi.org/10.1145/3448016.3452828
https://doi.org/10.1145/3448016.3452828
Publikováno v:
SIGMOD Conference
Personalized PageRank (PPR) is a critical measure of the importance of a node t to a source node s in a graph. The Single-Source PPR (SSPPR) query computes the PPR's of all the nodes with respect to s on a directed graph $G$ with $n$ nodes and $m$ ed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c2b8868b48fd1d2ca84cc318aff2e4d
http://arxiv.org/abs/2101.03652
http://arxiv.org/abs/2101.03652
Publikováno v:
KDD
Inspired by the great success of machine learning in the past decade, people have been thinking about the possibility of improving the theoretical results by exploring data distribution. In this paper, we revisit a fundamental problem called Distribu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cda963a3199d86c507be49400a8d997
https://doi.org/10.1145/3394486.3403255
https://doi.org/10.1145/3394486.3403255
Publikováno v:
Zengfeng Huang
KDD
KDD
Personalized PageRank (PPR) is a widely used node proximity measure in graph mining and network analysis. Given a source node $s$ and a target node $t$, the PPR value $\pi(s,t)$ represents the probability that a random walk from $s$ terminates at $t$
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6de7ba46c0f319bec97c4182b9452f5
Autor:
Yufei Tao, Junhao Gan
Publikováno v:
Journal of Graph Algorithms and Applications. 22:297-327
A vertex separator, in general, refers to a set of vertices whose removal disconnects the original graph into subgraphs possessing certain nice properties. Such separators have proved useful for solving a variety of graph problems. The core contribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ddfccd924bd1d7207037daccaf23bca
https://doi.org/10.7155/jgaa.00471
https://doi.org/10.7155/jgaa.00471
Autor:
JUNHAO GAN1 j.gan@uq.edu.au, YUFEI TAO2 taoyf@cse.cuhk.edu.hk
Publikováno v:
ACM Transactions on Database Systems. Jul2017, Vol. 42 Issue 3, p1-45. 45p.
Autor:
Yufei Tao, Junhao Gan
Publikováno v:
ACM Transactions on Database Systems. 42:1-45
DBSCAN is a method proposed in 1996 for clustering multi-dimensional points, and has received extensive applications. Its computational hardness is still unsolved to this date. The original KDD‚96 paper claimed an algorithm of O ( n log n ) ”aver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1792ab9d2fe4b07f655f04f6028ee8a5
https://doi.org/10.1145/3083897
https://doi.org/10.1145/3083897