Clustering for heterogeneous information networks with extended star-structure
Sign Up to like & getrecommendations! Published in 2019 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-019-00626-2
Abstract: Clustering of objects in a heterogeneous information network, where different types of objects are linked to each other, is an important problem in heterogeneous information network analysis. Several existing clustering approaches deal with star-structured information… read more here.
Keywords: information networks; information; heterogeneous information; star structure ... See more keywords
Minimized-cost cube query on heterogeneous information networks
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Combinatorial Optimization"
DOI: 10.1007/s10878-015-9967-6
Abstract: Data cube is the foundation of on-line analytical processing (OLAP), which can provide users with data views from different perspectives and granularities. Heterogeneous information networks consist of multiple types of nodes and edges which represent… read more here.
Keywords: information networks; cost; heterogeneous information; cube query ... See more keywords
Identification of information networks in stock markets
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Economic Dynamics and Control"
DOI: 10.1016/j.jedc.2021.104217
Abstract: Abstract We introduce a novel method to identify information networks in stock markets, which explicitly accounts for the impact of public information on investor trading decisions. We show that public information has a clear effect… read more here.
Keywords: networks stock; information networks; stock markets; identification information ... See more keywords
Biased information networks
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DOI: 10.1038/s41562-019-0760-x
Abstract: The decisions we make are partly based on the information we receive. However, not everybody is exposed to the same information when making a decision, such as which party to vote for. Understanding how information… read more here.
Keywords: information networks; information; influence; decision making ... See more keywords
Embedding Learning with Events in Heterogeneous Information Networks
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2017.2733530
Abstract: In real-world applications, objects of multiple types are interconnected, forming Heterogeneous Information Networks. In such heterogeneous information networks, we make the key observation that many interactions happen due to some event and the objects in… read more here.
Keywords: information networks; information; heterogeneous information; bold bold ... See more keywords
GraphInception: Convolutional Neural Networks for Collective Classification in Heterogeneous Information Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2019.2947458
Abstract: Collective classification has attracted considerable attention in the last decade, where the labels within a group of instances are correlated and should be inferred collectively, instead of independently. Conventional approaches on collective classification mainly focus… read more here.
Keywords: information networks; relational features; classification heterogeneous; collective classification ... See more keywords
Toward Tweet Entity Linking With Heterogeneous Information Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3068093
Abstract: Twitter, a microblogging platform, has developed into an increasingly invaluable information source, where millions of users post a great quantity of tweets with various topics per day. Heterogeneous information networks consisting of multi-type objects and… read more here.
Keywords: information; heterogeneous information; tweet entity; information networks ... See more keywords
Counter-Intuitive Characteristics of Rational Decision-Making Using Biased Inputs in Information Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/ACM Transactions on Networking"
DOI: 10.1109/tnet.2021.3075430
Abstract: We consider an information network comprised of nodes that are: rational-information-consumers (RICs) and/or biased-information-providers (BIPs). Making the reasonable abstraction that any external event is reported as an answer to a logical statement, we model each… read more here.
Keywords: information networks; tex math; inline formula; information ... See more keywords
Aspect-Aware Graph Attention Network for Heterogeneous Information Networks.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3213799
Abstract: Graph Convolutional Networks (GCNs) derive inspiration from recent advances in computer vision, by stacking layers of first-order filters followed by a nonlinear activation function to learn entity or graph embeddings. Although GCNs have been shown… read more here.
Keywords: information; network; aware graph; information networks ... See more keywords