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Graph Neural Networks for Natural Language Processing: A Survey
[article]
2021
arXiv
pre-print
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In this survey, we present a comprehensive overview onGraph Neural Networks(GNNs) for Natural Language Processing. ...
We propose a new taxonomy of GNNs for NLP, whichsystematically organizes existing research of GNNs for NLP along three axes: graph construction,graph representation learning, and graph based encoder-decoder ...
Globally normalized transition-based neural networks. ...
arXiv:2106.06090v1
fatcat:zvkhinpcvzbmje4kjpwjs355qu
Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs
[article]
2021
arXiv
pre-print
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We also briefly discuss the future directions for knowledge graph reasoning. ...
In this survey, we take a thorough look at the development of the symbolic, neural and hybrid reasoning on knowledge graphs. ...
Neural-enhanced Symbolic Reasoning Neural-enhanced symbolic reasoning still parses the given question into a query graph. ...
arXiv:2010.05446v5
fatcat:tc6fowebkzbv7df3cjyhkcu6uq
Learning an Executable Neural Semantic Parser
[article]
2018
arXiv
pre-print
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The generation process is modeled by structured recurrent neural networks, which provide a rich encoding of the sentential context and generation history for making predictions. ...
The parser generates tree-structured logical forms with a transition-based approach which combines a generic tree-generation algorithm with domain-general operations defined by the logical language. ...
Neural Semantic Parsing Framework We present a neural-network based semantic parser that maps an utterance into a logical form, which can be executed in the context of a knowledge base to produce a response ...
arXiv:1711.05066v2
fatcat:afikadyvarevvjit7adoscsx7u
Towards Expectation-Maximization by SQL in RDBMS
[article]
2021
arXiv
pre-print
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In this paper, we provide an SQL solution that has the potential to support different machine learning modelings. ...
It is important to note that the SQL'99 recursion cannot be used to handle such a while-loop since the M-step is non-monotonic. ...
We show that users can build model-based view by SQL recursive query with limited enhancement and the support of vector/matrix data type. Model-based View in RDBMS. ...
arXiv:2101.09094v1
fatcat:cidssfb2grffzkyddqbldtwmgi
Integrating flexibility and fuzziness into a question driven query model
2018
Information Sciences
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how to use SQL. ...
Further, a relational database management system supports a structured query language (SQL) for data processing, and it is not possible to access and retrieve data from a relational database without knowing ...
Neural Networks tend to find hidden links between the input. ...
doi:10.1016/j.ins.2017.11.049
fatcat:gh5f2eyppfbdfd6xzg32v7hmj4
Topic evolution and social interactions
2006
Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06
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By viewing the evolution of topics as a Markov chain, we estimate a Markov transition matrix of topics by leveraging social interactions and topic semantics. ...
We propose a method for discovering the dependency relationships between the topics of documents shared in social networks using the latent social interactions, attempting to answer the question: given ...
P (ti|tj) which are required for deriving the Markov transition matrix Γ. ...
doi:10.1145/1183614.1183653
dblp:conf/cikm/ZhouJZG06
fatcat:dykfrwdol5an7a3kc63ztke4ca
Systematic Literature Review over IDPS, Classification and Application in its Different Areas
2021
STATISTICS, COMPUTING AND INTERDISCIPLINARY RESEARCH
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Network security is vital for any organization connected to the Internet. ...
Anomaly-based Intrusion Detection Systems (AIDS). ...
Acknowledgement Authors are thankful to the Editorial Team for their constructive support. ...
doi:10.52700/scir.v3i2.58
fatcat:xrczlxjg5ncclf2ftxyw3y5zce
Detecting Design Patterns by Learning Embedded Code Features
2021
figshare.com
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Many algorithms are being used in embeddings, such as distance matrix, principal component analysis or neural networks. ...
During the parsing phase, the design pattern visuals and the source code are parsed and matched. ...
doi:10.6084/m9.figshare.14686989.v1
fatcat:wykzqmsewnd5vo2phtms74etsy
Multi-Task Learning in Natural Language Processing: An Overview
[article]
2021
arXiv
pre-print
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However, deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...
In [47] , a transition-based semantic parsing system is trained jointly on different parsing tasks, including Abstract Meaning Representation (AMR) [4] , Semantic Dependency Parsing (SDP) [88] , and ...
Training deep neural networks on a large dataset also asks for immense computing power as well as huge time and storage budget. ...
arXiv:2109.09138v1
fatcat:hlgzjykuvzczzmsgnl32w5qo5q
A Survey on Deep Reinforcement Learning for Data Processing and Analytics
[article]
2022
arXiv
pre-print
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Finally, we discuss key challenges and future directions for applying DRL in data processing and analytics. ...
Next, we survey and review DRL for data processing and analytics from two perspectives, systems and applications. ...
Earlier work [14] using generic autoencoder model for semantic parsing with Softmax as the final layer may generate unnecessarily large output spaces for SQL query generation tasks. ...
arXiv:2108.04526v3
fatcat:kcusgp7jzfbf7ov5os7gwf2e6i
Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges
[article]
2020
arXiv
pre-print
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Deep Learning (DL) techniques for Natural Language Processing have been evolving remarkably fast. ...
Then, we present the state-of-the-art practices and discuss their challenges with some recommendations for practitioners and researchers as well. ...
., code2vec [11] and code2seq [10] ) have also proposed to use AST paths as a representation for code, in which the extracted paths would be aggregated using an attention-based deep neural network. ...
arXiv:2002.05442v1
fatcat:bt7dtzrcnjfk5jn6kmin2ruqii
QUANTUM-INSPIRED ARTIFICIL NEURAL NETWORKS AND EVOLUTIONARY ALGORITHMS METHODS APPLIED TO MODELING OF THE POLISH ELECTRIC POWER EXCHANGE USING THE DAY-AHEAD MARKET DATA
2018
Information System in Management
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ANN , Difference -difference between the adders of net 1 for the artificial neural network and the Quantum Artificial Neural Network. ...
The results obtained for the neural model and for the Evolutionary Algorithm inspired by quantum computing were also discussed and were verified on the example of enhancing parameters of the model of the ...
In the paper, we propose document clustering for label selection. ...
doi:10.22630/isim.2018.7.3.18
fatcat:hdnawbi43vbatajygssciknmvq
Neural Approaches to Conversational AI
[article]
2019
arXiv
pre-print
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For each category, we present a review of state-of-the-art neural approaches, draw the connection between them and traditional approaches, and discuss the progress that has been made and challenges still ...
The present paper surveys neural approaches to conversational AI that have been developed in the last few years. ...
are an extension for recurrent neural networks (RNNs). ...
arXiv:1809.08267v3
fatcat:j57xlm4ogferdnrpfs4f2jporq
Data Semantics
[chapter]
2017
Encyclopedia of GIS
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Web Mapping and Web Cartography Web Services, Geospatial
Cross-References Internet-Based Spatial Information Retrieval Internet GIS ...
Cross-References Data Infrastructure, Spatial Geography Markup Language (GML) Metadata and Interoperability, Geospatial National Spatial Data Infrastructure (NSDI) OGC's Open Standards for Geospatial Interoperability ...
Queries are parsed and disseminated into the sensor network at the base station and a spatial query over a sensor network can return a set of attributes or an aggregation of attributes of sensors in any ...
doi:10.1007/978-3-319-17885-1_100256
fatcat:npcac6ns2zdjfokmwpmzb2s6km
Evaluation of Logic Programs with Built-Ins and Aggregation: A Calculus for Bag Relations
[article]
2020
arXiv
pre-print
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We present a scheme for translating logic programs, which may use aggregation and arithmetic, into algebraic expressions that denote bag relations over ground terms of the Herbrand universe. ...
To evaluate queries against these relations, we develop an operational semantics based on term rewriting of the algebraic expressions. ...
We focus on how our term rewriting approach is able to handle the neural network example (lines 6-14) . ...
arXiv:2010.10503v1
fatcat:2lvy267bffdo3nbq7lsbqajnuy
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