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Harnessing relationships for domain-specific subgraph extraction: A recommendation use case
2016
2016 IEEE International Conference on Big Data (Big Data)
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We demonstrate the applicability of this approach for a recommendation use case on two domains, i.e. movie and book. ...
For example, a movie or a book recommendation system would require a subgraph that comprises knowledge relevant to the specific domain. ...
Recommendation is a well-suited use case for domain-specific subgraph extraction as it considers the item relatedness among in-domain entities. ...
doi:10.1109/bigdata.2016.7840663
dblp:conf/bigdataconf/LalithsenaKS16
fatcat:d5zpdm4hj5anllx3hin5yi3xkq
Domain-specific hierarchical subgraph extraction: A recommendation use case
2017
2017 IEEE International Conference on Big Data (Big Data)
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We show the effectiveness of our approach with a recommendation use case for movie and book domains. ...
Furthermore, the presented approach outperforms the recommendation results obtained with a stateof-the-art domain-specific subgraph extraction technique which uses supervised learning. ...
Furthermore, to show the effectiveness on applications using KGs, we evaluated the quality of the domain-specific subgraph extracted with a recommendation use case. ...
doi:10.1109/bigdata.2017.8257982
dblp:conf/bigdataconf/LalithsenaPKS17
fatcat:ctmcha5bs5dolkitvqpwkesoiu
Extraction and Analysis of Fictional Character Networks
2019
ACM Computing Surveys
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A character network is a graph extracted from a narrative, in which vertices represent characters and edges correspond to interactions between them. ...
We then review the descriptive tools used to characterize character networks, with a focus on the way they are interpreted in this context. ...
Acknowledgments The authors would like to thank the anonymous reviewers for their work and feedback, which helped significantly improve this article. Part of this work was funded by Agorantic FR 3621. ...
doi:10.1145/3344548
fatcat:zujg55eixfct7blvj6lxwo4usq
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
[article]
2018
arXiv
pre-print
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To address this, we present a combination of techniques that harness knowledge graphs to improve performance on the NLI problem in the science questions domain. ...
While there are many open knowledge bases that contain various types of reasoning information, their use for NLI has not been well explored. ...
This work harnesses WordNet as the external knowledge for NLI. WordNet, however, is a lexical database restricted to a small number of linguistic relationships among terms. Furthermore, Chen et al. ...
arXiv:1809.05724v2
fatcat:7dolmjp3rvgxljilc6qanqsgvy
Knowledge Graphs and Knowledge Networks: The Story in Brief
[article]
2020
arXiv
pre-print
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However, for dynamic real-world applications such as social networks, recommender systems, computational biology, relational knowledge representation has emerged as a challenging research problem where ...
Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. ...
Recent studies in domain-specific subgraph extraction have significantly contributed to improving the efficiency and quality of information extraction and complex task-specific algorithms by capturing ...
arXiv:2003.03623v1
fatcat:zle7g626mzeqrkmobgrr6xtfae
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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To address this, we present a combination of techniques that harness external knowledge to improve performance on the NLI problem in the science questions domain. ...
While there are many open knowledge bases that contain various types of reasoning information, their use for NLI has not been well explored. ...
a subgraph from ConceptNet for a given premise p and a hypothesis h. ...
doi:10.1609/aaai.v33i01.33017208
fatcat:chb6qvwgrzav5f5x2olzavo5bi
Harnessing the Power of Ego Network Layers for Link Prediction in Online Social Networks
[article]
2021
arXiv
pre-print
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Finally, we show that social-awareness can be used in place of using a classifier (which may be costly or impractical) for targeting a specific category of users. ...
Being able to recommend links between users in online social networks is important for users to connect with like-minded individuals as well as for the platforms themselves and third parties leveraging ...
This implies that some nodes are domain-specific (in our case, gaming-related), while others are generic. Domain-specific nodes are homogeneous, since they share a common interest. ...
arXiv:2109.09190v1
fatcat:m2ock43efzd7vppwjkmqhkvz6y
Research Directions for Big Data Graph Analytics
2015
2015 IEEE International Congress on Big Data
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In the era of big data, interest in analysis and extraction of information from large data graphs is increasing rapidly. ...
Still, the need to provide answers even for very large graphs is driving the research. Progress, trends and directions for future research are presented. ...
In other situations, the relationships between data items is what is of most importance. In such cases, the data may be captured in a graph. ...
doi:10.1109/bigdatacongress.2015.132
dblp:conf/bigdata/MillerRKF15
fatcat:ws7anjfh3nh3lh7aw44cnwo4hm
Scalable Combinatorial Tools for Health Disparities Research
2014
International Journal of Environmental Research and Public Health
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While standard techniques can scrutinize at most a handful of parameters for obvious dependencies, combinatorial methods are able to extract latent signal from a sea of even only modest correlations spread ...
The public health exposome is used as a contemporary focus for addressing the complex nature of this subject. on the exposome paradigm [2], and is aimed at describing the effects of multiple and cumulative ...
We thank the anonymous reviewers for their thoughtful critiques and helpful comments. ...
doi:10.3390/ijerph111010419
pmid:25310540
pmcid:PMC4210988
fatcat:smmhbbw44rh45pxn73i46mmeie
Graph Learning for Cognitive Digital Twins in Manufacturing Systems
[article]
2021
arXiv
pre-print
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Digital twins incorporate a physical twin, a digital twin, and the connection between the two. ...
Benefits of using digital twins, especially in manufacturing, are abundant as they can increase efficiency across an entire manufacturing life-cycle. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect views of our funding agencies. ...
arXiv:2109.08632v1
fatcat:63kqrdg2hzakpj3jplptuayyjy
Query-driven on-the-fly knowledge base construction
2017
Proceedings of the VLDB Endowment
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QKBfly is based on a semantic-graph representation of sentences, by which we perform three key IE tasks, namely named-entity disambiguation, co-reference resolution and relation extraction, in a light-weight ...
To overcome both of these limitations, we propose a novel approach to build on-the-fly knowledge bases in a query-driven manner. ...
As an extrinsic use-case, we harness QKBfly for KB-QA. ...
doi:10.14778/3151113.3151119
fatcat:tll2ue5gmraxbfbrc3r5b7sdri
Semantically-Guided Clustering of Text Documents via Frequent Subgraphs Discovery
[chapter]
2011
Lecture Notes in Computer Science
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In this paper we introduce and analyze two improvements to GDClust [1], a system for document clustering based on the co-occurrence of frequent subgraphs. ...
Text documents are transformed to hierarchical document-graphs, and an efficient graph-mining technique is used to find frequent subgraphs. ...
for organizing the numerous documents available to us on a daily basis. ...
doi:10.1007/978-3-642-21916-0_44
fatcat:2ynpfgcihng5ljccbkl5pcnoqu
Emerging, Collective Intelligence for Personal, Organisational and Social Use
[chapter]
2011
Studies in Computational Intelligence
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In [19] tags and visual information together with geo-location are used for objects (e.g. monuments) and events extraction. ...
The exploitation of the emerging Collective Intelligence results is showcased in two distinct case studies: an Emergency Response and a Consumers Social Group 3 case study. ...
number of within-subgraph connections for subgraph S, and outd(S) stands for the number of connections from subgraph nodes to the rest of the graph. ...
doi:10.1007/978-3-642-20344-2_20
fatcat:crgix2grbvfupaht5mp3cjriii
Mining Biomedical Ontologies and Data Using RDF Hypergraphs
2013
2013 12th International Conference on Machine Learning and Applications
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By representing both ontologies and data using RDF hypergraphs, and subsequently transforming the hypergraphs to corresponding bipartite forms, we provide a generalized data mining method that scales beyond ...
in a systematic and scalable way. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the supporting institutions. ...
doi:10.1109/icmla.2013.31
dblp:conf/icmla/LiuDJLS13
fatcat:ftgbjka5lnb7vkc53utif4pkje
HAR: Hub, Authority and Relevance Scores in Multi-Relational Data for Query Search
[chapter]
2012
Proceedings of the 2012 SIAM International Conference on Data Mining
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can incorporate input query vectors to handle query-specific search; (ii) show existence and uniqueness of such limiting probabilities so that they can be used for query search effectively; and (iii) ...
In this paper, we propose a framework HAR to study the hub and authority scores of objects, and the relevance scores of relations in multi-relational data for query search. ...
Rendle el al. proposed a tensor factorization model to exploit the ternary relationships in tagging data and personalize the tag recommender [19] . Kolda et al. ...
doi:10.1137/1.9781611972825.13
dblp:conf/sdm/LiNY12
fatcat:kadu6nbcbngcfgvdzvhulrk7l4
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