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Multi-Document Information Consolidation (Dagstuhl Seminar 19182)

Ido Daga, Iryna Gurevych, Dan Roth, Amanda Stent, Michael Wagner
2019 Dagstuhl Reports  
and visualize multi-document repositories for decision support; and 4) how to do information validation on multi-document repositories.  ...  This report documents the program and the outcomes of Dagstuhl Seminar 19182 "Multi-Document Information Consolidation".  ...  visualize multi-document repositories for decision support; and 4) how to do information validation on multi-document repositories.  ... 
doi:10.4230/dagrep.9.4.124 dblp:journals/dagstuhl-reports/DaganGRS19 fatcat:lej5rn6i4vhphjun6hw4uj4sra

Unsupervised Key-phrase Extraction and Clustering for Classification Scheme in Scientific Publications [article]

Xiajing Li, Marios Daoutis
2021 arXiv   pre-print
In this paper we investigate possible ways of automating parts of the SM/SR process, i.e. that of extracting keywords and key-phrases from scientific documents using unsupervised methods, which are then  ...  also explore how clustering can be used to group related key-phrases.  ...  (Q2), as well as the effect of clustering for grouping semantically related key-phrases (Q3).  ... 
arXiv:2101.09990v2 fatcat:n6vnkvwxlbc4bogzx5ootfyyya

Text Analytics in Social Media [chapter]

Xia Hu, Huan Liu
2012 Mining Text Data  
The rapid growth of online social media in the form of collaborativelycreated content presents new opportunities and challenges to both producers and consumers of information.  ...  In this chapter, we first introduce the background of traditional text analytics and the distinct aspects of textual data in social media.  ...  For example, tag "Japan Earthquake" does not contain any words or phrases related to "Nuclear Crisis" while we learn that these two events are related from recent news.  ... 
doi:10.1007/978-1-4614-3223-4_12 fatcat:ynmfabrhpjf6vils663o3rs2za

ERMIS: Extracting Knowledge from Unstructured Big Data for Supporting Business Decision Making [chapter]

Christos Alexakos, Konstantinos Arvanitis, Andreas Papalambrou, Thomas Amorgianiotis, George Raptis, Nikolaos Zervos
2016 IFIP Advances in Information and Communication Technology  
The Query Processing Orchestrator is a Multi-Agent System and it is responsible for scheduling all tasks related to query processing, such as analysis to extract relevant terms and periodic checks to update  ...  The extraction of knowledge related to a user's query comes with the semantic inference to the axioms stored in the Knowledge Base.  ... 
doi:10.1007/978-3-319-44944-9_54 fatcat:pa6jgz4z35bx7mjidmlnil6mpu

A Multi-scale Visual Analytics Approach for Exploring Biomedical Knowledge [article]

Fahd Husain, Rosa Romero-Gomez, Emily Kuang, Dario Segura, Adamo Carolli, Lai Chung Liu, Manfred Cheung, Yohann Paris
2021 arXiv   pre-print
This paper describes an ongoing multi-scale visual analytics approach for exploring and analyzing biomedical knowledge at scale.We utilize global and local views, hierarchical and flow-based graph layouts  ...  , multi-faceted search, neighborhood recommendations, and document visualizations to help researchers interactively explore, query, and analyze biological graphs against the backdrop of biomedical knowledge  ...  The neighborhood of a given document is taken as the set of semantically similar documents within the corpus [33] .  ... 
arXiv:2109.06828v2 fatcat:b6ej4vtx3fgzhpujpks56j5mwe

Visual Analysis and Knowledge Discovery for Text [chapter]

Christin Seifert, Vedran Sabol, Wolfgang Kienreich, Elisabeth Lex, Michael Granitzer
2013 Large-Scale Data Analytics  
Besides introducing human knowledge and visual pattern recognition into the analytical process, it provides the possibility to improve the performance of automatic methods through user feedback.  ...  This chapter provides an overview of data visualization methods for gaining insight into large, heterogeneous, dynamic textual data sets.  ...  Semantic Enrichment Semantic enrichment extracts domain-specific semantics from single documents and enriches each document with external knowledge.  ... 
doi:10.1007/978-1-4614-9242-9_7 fatcat:5ti6ubvuj5d5dhfjg6eyiyld6m

Semantic Data Ingestion for Intelligent, Value-Driven Big Data Analytics

Jeremy Debattista, Judie Attard, Rob Brennan
2018 2018 4th International Conference on Big Data Innovations and Applications (Innovate-Data)  
In this position paper we describe a conceptual model for intelligent Big Data analytics based on both semantic and machine learning AI techniques (called AI ensembles).  ...  These processes are linked to business outcomes by explicitly modelling data value and using semantic technologies as the underlying mode for communication between the diverse processes and organisations  ...  ACKNOWLEDGEMENT We would like to thank Giovanni Schiuma, Markus Helfurt, Pieter De Leenheer, Eamonn Clinton, Diego Calvanese, Christian Dirschl, Ismael Caballero, Hans Viehmann, and Rico Richter for their  ... 
doi:10.1109/innovate-data.2018.00008 dblp:conf/obd/DebattistaAB18 fatcat:3hiyg2rd4fh2hdx37jelozkz5e

Ranking Documents Based on the Semantic Relations Using Analytical Hierarchy Process

Ali I., Hesham A., Rabab S.
2016 International Journal of Advanced Computer Science and Applications  
In this work, we present a method for utilizing genealogical information from ontology to find the suitable hierarchical concepts for query extension, and ranking web pages based on semantic relations  ...  So, it provides an accurate solution for ranking documents when compared to the three common methods.  ...  The second method is a ranking process for documents based on the semantic relation between document contents and the query terms. II.  ... 
doi:10.14569/ijacsa.2016.070222 fatcat:sbhxaidnavhy5jq5hjd4fg4b4u

A Consolidated System for Robust Multi-Document Entity Risk Extraction and Taxonomy Augmentation [article]

Berk Ekmekci, Eleanor Hagerman, Blake Howald
2019 arXiv   pre-print
As the taxonomy expands, the amount of relevant information increases and multi-sentence extractions become more preferred, but this is tempered against entity-risk relations become more indirect.  ...  We introduce a hybrid human-automated system that provides scalable entity-risk relation extractions across large data sets.  ...  Acknowledgments Thank you to anonymous reviewers from NAACL Industry Track as well as Matt Machado, Nathan Maynes, and Scott McFadden for support and feedback.  ... 
arXiv:1909.10368v1 fatcat:55x3yz2zifafhlf56rzyt7dr64

Visual Exploration of Spatial and Temporal Variations of Tweet Topic Popularity [article]

Jie Li, Siming Chen, Gennady Andrienko, Natalia Andrienko
2018 Eurographics Conference on Visualization  
Our approach includes an analytical pipeline and a multi-view visualization tool.  ...  As attempts of topic extraction from very short texts like tweets may not produce meaningful results, we aggregate the texts prior to applying topic modelling techniques.  ...  There are about 6900 different hashtags; we created for each hashtag 78 documents (78 weeks) for topic extraction.  ... 
doi:10.2312/eurova.20181105 dblp:conf/vissym/LiCAA18 fatcat:urkb7kc6lvbs5eav5qfie3gydq

INDREX: In-database relation extraction

Torsten Kilias, Alexander Löser, Periklis Andritsos
2015 Information Systems  
Therefore, end users often desire a single system for both analytical and relation extraction tasks.  ...  Typically, the user performs this task with two separate systems, a relation extraction system and an SQL-based query engine for analytical tasks.  ...  Related work We abstract the task of relation extraction as an iterative multi-label multi-class classification task.  ... 
doi:10.1016/ fatcat:jrweeola2ffanclmmfw5bpdff4

Guest Editorial: Introduction to the Special Issue on Advances in Semantic Computing

Phillip C.-Y. Sheu, Arif Ghafoor
2015 IEEE Transactions on Emerging Topics in Computing  
Furthermore, it is challenging to add related entities to texts since it involves the extraction of key terms, finding the related entities for each key term, and the aggregation of related entities.  ...  While Semantic Computing was first substantiated in text analytics, it has the potential for much broader applications.  ... 
doi:10.1109/tetc.2015.2432332 fatcat:luubzsq7jzbljnnitdwntdnhnm

Big Text Visual Analytics in Sensemaking

Lauren Bradel, Nathan Wycoff, Leanna House, Chris North
2015 2015 Big Data Visual Analytics (BDVA)  
), forage for new, relevant documents as implied by the interactions, and place them in context of the user's existing spatial layout.  ...  To address this issue, we applied the multi-model semantic interaction (MSI) technique, which leverages user interactions to aid in the display layout (as was seen in previous semantic interaction work  ...  New entities are attached to the document in which they were found, and then the rest of known documents are searched for the new entities in order to relate them to one another.  ... 
doi:10.1109/bdva.2015.7314287 dblp:conf/bdva/BradelWHN15 fatcat:k7eq7jm2gjhv5p6lsfve6cnnhm

A Survey of Data Representation for Multi-Modality Event Detection and Evolution

Kejing Xiao, Zhaopeng Qian, Biao Qin
2022 Applied Sciences  
Next, we discuss the techniques of data representation for event detection, including textual, visual, and multi-modality content. Finally, we review event evolution under multi-modality data.  ...  The rapid growth of online data has made it very convenient for people to obtain information. However, it also leads to the problem of "information overload".  ...  MT-AOG models latent topic structures by leveraging a context sensitive grammar that can describe the hierarchical composition of news topics by semantic elements about people involved, related places,  ... 
doi:10.3390/app12042204 fatcat:5gpezz6yhjejlmdzr5fhpgka6m

Cross-media Event Extraction and Recommendation

Di Lu, Clare Voss, Fangbo Tao, Xiang Ren, Rachel Guan, Rostyslav Korolov, Tongtao Zhang, Dongang Wang, Hongzhi Li, Taylor Cassidy, Heng Ji, Shih-fu Chang (+5 others)
2016 Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations  
It also recommends events related to the user's ongoing search based on previously selected attribute values and dimensions of events being viewed.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.  ... 
doi:10.18653/v1/n16-3015 dblp:conf/naacl/LuVTRGKZWLCJCHW16 fatcat:kxehxhclqzacpa6rtxijgqgsqy
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