Results 1 - 10
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107
Link Prediction for Annotation Graphs using Graph Summarization
"... Abstract. Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences where genes or proteins are annotated with controlled vocabulary terms (CV terms) from ontologies. The W3C Linking Open Data (LOD) initiative and semantic Web technologies a ..."
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Cited by 9 (2 self)
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in annotation graph datasets. In this paper, we propose a novel approach for link prediction; it is a preliminary task when discovering more complex patterns. Our prediction is based on a complementary methodology of graph summarization (GS) and dense subgraphs (DSG). GS can exploit and summarize knowledge
Assessing drug target association using semantic linked data
- PLoS Comput Biology
"... The rapidly increasing amount of public data in chemistry and biology provides new opportunities for large-scale data mining for drug discovery. Systematic integration of these heterogeneous sets and provision of algorithms to data mine the integrated sets would permit investigation of complex mecha ..."
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Cited by 9 (2 self)
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mechanisms of action of drugs. In this work we integrated and annotated data from public datasets relating to drugs, chemical compounds, protein targets, diseases, side effects and pathways, building a semantic linked network consisting of over 290,000 nodes and 720,000 edges. We developed a statistical
Frontal brain activity during episodic and semantic retrieval: Insights from event-related potentials
- Journal of Cognitive Neuroscience
, 1999
"... Previous neuropsychological and neuroimaging results have implicated the prefrontal cortex in memory retrieval, although its precise role is unclear. In the present study, we examined patterns of brain electrical activity during retrieval of episodic and semantic memories. In the episodic retrieval ..."
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Cited by 14 (1 self)
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identiªable as the P3a potential. Based on prior research linking P3a with novelty detection and with the frontal lobes, we predicted that P3a would be reduced to the extent that novelty detection and memory retrieval interfere with each other. Results during episodic and semantic retrieval tasks were
Top-N Recommendations from Implicit Feedback leveraging Linked Open Data
"... The advent of the Linked Open Data (LOD) initiative gave birth to a variety of open knowledge bases freely accessible on the Web. They provide a valuable source of information that can improve conventional recommender systems, if properly exploited. In this paper we present SPrank, a novel hybrid re ..."
Abstract
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Cited by 13 (4 self)
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The advent of the Linked Open Data (LOD) initiative gave birth to a variety of open knowledge bases freely accessible on the Web. They provide a valuable source of information that can improve conventional recommender systems, if properly exploited. In this paper we present SPrank, a novel hybrid
2011) Exploring and exploiting disease interactions from multi-relational gene and phenotype networks
- PLoS One
"... The availability of electronic health care records is unlocking the potential for novel studies on understanding and modeling disease co-morbidities based on both phenotypic and genetic data. Moreover, the insurgence of increasingly reliable phenotypic data can aid further studies on investigating t ..."
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Cited by 7 (1 self)
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and clinical realities. Our results show a marked difference between the well defined structure of genetic relationships and the chaotic co-morbidity network, but also highlight clear interdependencies. We demonstrate the power of these dependencies by proposing a novel multi-relational link prediction method
Extracting key terms from noisy and multi-theme documents
, 2009
"... We present a novel method for key term extraction from text documents. In our method, document is modeled as a graph of semantic relationships between terms of that document. We exploit the following remarkable feature of the graph: the terms related to the main topics of the document tend to bunch ..."
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Cited by 36 (3 self)
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We present a novel method for key term extraction from text documents. In our method, document is modeled as a graph of semantic relationships between terms of that document. We exploit the following remarkable feature of the graph: the terms related to the main topics of the document tend to bunch
Mining Cohesive Patterns from Graphs with Feature Vectors
"... The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to graph data, where nodes represent entities, edges relationships between entities, and feature vectors associated with the ..."
Abstract
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Cited by 32 (1 self)
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The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to graph data, where nodes represent entities, edges relationships between entities, and feature vectors associated
Scalable Integration and Processing of Linked Data ∗
, 2011
"... The goal of this tutorial is to introduce, motivate and detail techniques for integrating heterogeneous structured data from across the Web. Inspired by the growth in Linked Data publishing, our tutorial aims at educating Web researchers and practitioners about this new publishing paradigm. The tuto ..."
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. The tutorial will show how Linked Data enables uniform access, parsing and interpretation of data, and how this novel wealth of structured data can potentially be exploited for creating new applications or enhancing existing ones. As such, the tutorial will focus on Linked Data publishing and related Semantic
Who Will Follow Your Shop? Exploiting Multiple Information Sources in Finding Followers
"... Abstract. WuXianGouXiang is an O2O(offline to online and vice versa)-based mobile application that recommends the nearby coupons and deals for users, by which users can also follow the shops they are interested in. If the potential followers of a shop can be discovered, the merchant’s targeted adver ..."
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advertising can be more effective and the recom-mendations for users will also be improved. In this paper, we propose to predict the link relations between users and shops based on the following behavior. In order to better model the characteristics of the shops, we first adopt Topic Modeling to analyze
A Shortest-path Method for Arc-factored Semantic Role Labeling
"... We introduce a Semantic Role Labeling (SRL) parser that finds semantic roles for a predicate together with the syntactic paths linking predicates and arguments. Our main contribution is to formulate SRL in terms of shortest-path inference, on the as-sumption that the SRL model is restricted to arc-f ..."
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-factored features of the syntactic paths behind semantic roles. Overall, our method for SRL is a novel way to ex-ploit larger variability in the syntactic re-alizations of predicate-argument relations, moving away from pipeline architectures. Experiments show that our approach im-proves the robustness
Results 1 - 10
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107