Text Graphs & Natural Language 2014


See also:

Dynamic Topic ModelingSentence Summarization | Text Graphs & Natural Language 2015


Graph-based methods for natural language processing and understanding—A survey and analysis MT Mills, NG Bourbakis – Systems, Man, and Cybernetics: …, 2014 – ieeexplore.ieee.org … 1 Graph-Based Methods for Natural Language Processing and Understanding—A Survey and Analysis … Index Terms—Graph methods, natural language processing (NLP), natural language understanding (NLU). I. INTRODUCTION … Cited by 4 Related articles All 2 versions

Bdgs: A scalable big data generator suite in big data benchmarking Z Ming, C Luo, W Gao, R Han, Q Yang, L Wang… – Advancing Big Data …, 2014 – Springer … systems, big data generators should support a diversity data types (structured, semi-structured and unstructured) and sources (table, text, graph, etc … In machine learning and natural language processing, a topic model is a type of statistics designed to discover the abstract topics … Cited by 23 Related articles All 8 versions

Tass 2013-a second step in reputation analysis in Spanish J Villena Román, J García Morera, S Lana Serrano… – 2014 – rua.ua.es … Sentiment analysis is the application of natural language processing and text analytics to identify and extract subjective information from texts. … Thus, a metric is used for calculating the similarity between the text graph to classify and the different topic graphs. … Cited by 8 Related articles All 7 versions

Scrutable plan enactment via argumentation and natural language generation MW Caminada, R Kutlak, N Oren… – Proceedings of the 2014 …, 2014 – dl.acm.org … The “Controller” connects Graphics Natural Language Generation Argumentation Controller UI Graph Text Query Arguments Arguments Commands Text + Graph Demonstrator Workflow KB (Arguments) Domain (Symbols to text mappings) Figure 1: Architecture … Cited by 3 Related articles All 7 versions

Mining semantic structures from syntactic structures in free text documents H Mousavi, D Kerr, M Iseli… – … Computing (ICSC), 2014 …, 2014 – ieeexplore.ieee.org Page 1. Mining Semantic Structures from Syntactic Structures in Free Text Documents Hamid Mousavi CSD, UCLA hmousavi@cs.ucla.edu Deirdre Kerr CRESST, UCLA dkerr@cse.ucla.edu Markus Iseli CRESST, UCLA iseli@cse.ucla.edu … Cited by 4 Related articles All 9 versions

Empirical studies of the value of conceptually explicit notations in collaborative learning DD Suthers – Knowledge cartography, 2014 – Springer … The experimental software had two main windows, one containing a workspace for creating either text, graph, or matrix representations, and the other … From this work we learned that online discourse will not be confined to the medium provided for natural language interaction: it … Cited by 16 Related articles All 11 versions

Centrality Measures for Non-Contextual Graph-Based Unsupervised Single Document Keyword Extraction N Schluter – Proceedings of TALN 2014 – anthology.aclweb.org … In the context of our text graph, the betweenness centrality can be seen as a measure of how the presentation of a … In Proceedings of the 2003 conference on Empirical methods in natural language processing, EMNLP ’03, p. 216–223, Stroudsburg, PA, USA : Association for … Cited by 4 Related articles All 6 versions

Multi-document Summarization by Extended Graph Text Representation and Importance Refinement U Mirchev, M Last – Innovative Document Summarization …, 2014 – books.google.com Page 50. 28 Chapter 2 Multi-Document Summarization by Extended Graph Text Representation and Importance Refinement Uri Mirchev Ben Gurion University of the Negev, Israel Mark Last Ben Gurion University of the Negev … Cited by 3 Related articles All 2 versions

Weighted archetypal analysis of the multi-element graph for query-focused multi-document summarization E Canhasi, I Kononenko – Expert systems with applications, 2014 – Elsevier … as edge weights. They take into account the global information and recursively calculate the sentence significance from the entire text graph rather than simply relying on unconnected individual sentences. Graph-based ranking … Cited by 19 Related articles All 4 versions

From requirements to UML models and back: how automatic processing of text can support requirements engineering M Landhäußer, SJ Körner, WF Tichy – Software Quality Journal, 2014 – Springer … AutoAnnotator only processes English texts but can be adapted easily for other languages as long as the underlying natural language processing tools … Changed and deleted elements can be identified in the text graph using the tracking edges for updating the text or removing … Cited by 5 Related articles All 7 versions

Person instance graphs for mono-, cross-and multi-modal person recognition in multimedia data: application to speaker identification in TV broadcast H Bredin, A Roy, VB Le, C Barras – International Journal of Multimedia …, 2014 – Springer … The expected output of such clustering is illustrated in the right part of Fig. 2. Clustering has been addressed in numerous scientific fields in the past: from graph mining and community detec- tion [30] to natural language processing and co-reference resolution [14]. … Cited by 4 Related articles All 5 versions

Survey on Graph and Cluster Based approaches in Multi-document Text Summarization YK Meena, A Jain, D Gopalani – Recent Advances and …, 2014 – ieeexplore.ieee.org … entire text (graph). Under the Hub/Authority framework it It uses effective Difficult to detect … [4] 1. Zhang, L. Sun, and Q. Zhou, “A cue-based hub-authority approach for multi-document text summarization, ” in Natural Language Processing and Knowledge Engineering, 2005. … Cited by 3 Related articles

Text-Mining, Structured Queries, and Knowledge Management on Web Document Corpora H Mousavi, M Atzori, S Gao, C Zaniolo – ACM SIGMOD Record, 2014 – dl.acm.org … Ease of access is achieved if the system can take users’ queries expressed in natural language and translate them into SPARQL queries … For instance, Figure 4 shows the Text- Graph for following sentence: Example Sentence: “Johann Sebastian Bach (31 March 1685 – 28 July … Cited by 1 Related articles All 4 versions

Survey in Textual Entailment S Ghuge, A Bhattacharya – Center for Indian Language Technology, …, 2014 – cfilt.iitb.ac.in … Here we illustrate the procedure to convert a natural language text to a depen- dency graph … For hypothesis graph H, and text graph T, a matching M is a mapping from the vertices of H to those of T. For vertex v in H, M(v) denotes its match in T. As is common in statistical machine … Cited by 2 Related articles

Extractive Text Summarisation using Graph Triangle Counting Approach: Proposed Method YA AL-Khassawneh, N Salim, OA Isiaka – researchgate.net … text graph, fabri- cated from cosine likeness, is considered an arrangement that offers the greatest summarisation presentation. Stochastic graph-based method was suggested in [19] for calculating comparative significance of documentary components for Natural Language … Related articles All 2 versions

An Automated Approach for Interpretation of Statistical Graphics A Mahmood, IS Bajwa, K Qazi – Intelligent Human-Machine …, 2014 – ieeexplore.ieee.org … The extracted information is represented in the form of natural language summaries using template based approach. … Then we have designed the natural language based templates for final interpretation of each class of area charts. II. … Related articles

Discovering Relations by Entity Search in Lightweight Semantic Text Graphs M Laclav?k, Š Dlugolinský, M Ciglan – Computing and Informatics, 2014 – laclavik.sk … The idea of building or extracting graphs from text is not new and it is used to accomplish many tasks in Natural Language Processing (NLP) [30] related to tasks in syntax like Part of Speech (POS … In [15], text graphs are used to create signed social network from text discussions. … Related articles All 4 versions

Knowledge Based Question Answering System Using Ontology R Mervin, A Jaya – ijesrt.com … The basic idea of QA systems in Natural Language Processing (NLP) is to provide correct answers to the questions for the user. … Natural language processing techniques are used for processing the question and also for answer extraction. … Related articles

Natural Language Generation from Graphs NT Dong, LB Holder – International Journal of Semantic Computing, 2014 – World Scientific Page 1. Natural Language Generation from Graphs … Keywords: RDF; graph; natural language generation. 1. Introduction Natural Language Generation (NLG) is a natural language processing task of gen- erating natural language from a computer representation of data. … Related articles

Researching persons & organizations: AWAKE: From text to an entity-centric knowledge base E Boschee, M Freedman, S Khanwalkar… – Big Data (Big Data), …, 2014 – ieeexplore.ieee.org … and entity disambiguation challenge is a significant current area of research in the field of natural language processing and … includes four dimensions to interpreting text: syntactic parsing, creating a simple propositional logical form called text graphs, understanding coreference … Related articles

Text summarization as an assistive technology F Hamid, P Tarau – Proceedings of the 7th International Conference on …, 2014 – dl.acm.org … There has been a comparatively new trend in Natural Language Processing that uses graph based ranking algo- rithms [3] to process texts and extract keywords or sen … We adapted their idea on text- graphs, which works with not only opinion-biased but also non-biased texts. … Related articles

Generating Annotated Graphs using the NLG Pipeline Architecture S Mahamood, W Bradshaw, E Reiter, NLG Arria – INLG 2014, 2014 – anthology.aclweb.org Proceedings of the 8th International Natural Language Generation Conference, pages 123–127, Philadelphia, Pennsylvania, 19-21 June 2014. … overall, and where messages should appear (for example, situational analysis text, diagnosis text, impact text, graph annotation, or a … Related articles All 8 versions

Discovering Relations By Entity Search In Semantic Text Graphs M Laclav?k, Š Dlugolinský, M Ciglan – cai.sk … The idea of building or extracting graphs from text is not new and it is used to accomplish many tasks in Natural Language Processing (NLP) [33] related to tasks in syntax like Part of Speech (POS … In [17], text graphs are used to create signed social network from text discussions. … Related articles

Graph-based techniques for tweet classification in Spanish H Cordobés de la Calle – 2014 – eprints.networks.imdea.org … of the well-known PageRank metric [3] to text graphs, has been used with remarkable success [7] to extract good representatives in text … As mentioned, this work makes use of the TASS2013 corpus, managed by SEPLN (Spanish Society for Natural Language Processing) for its … Related articles

Text Entailment and Machine Translation Evaluation S Gautam – 2014 – cfilt.iitb.ac.in … In Natural Language Processing (NLP), it plays a vital role. … Let, T be a Text graph, H be a Hypothesis graph and M(Matching) is a mapping which is used to map the vertices of T to vertices of H. For a vertex v in H, let the mapping of this vertex in T is M(v). Similar to Statistical … Related articles

An Ontology-Based Text Mining Method To Construct D-Matrix For Fault Detection And Diagnosis Using Graph Comparison … MMM Varma, J Nandimath – 2014 – ijiris.com … Keyword: Fault diagnosis ontology, D-matrix, Text Mining, Unstructured text, Graph comparison algorithm. … Ontology based text mining to develop D-Matrix conquered these impediments where regular natural language transforming algorithm were proposed to consequently …

Analysis and Classification of Constrained DNA Elements with N-gram Graphs and Genomic Signatures D Polychronopoulos, A Krithara, C Nikolaou… – Algorithms for …, 2014 – Springer … Traditionally, natural language processing methods based on n-grams (n-nucleotides correspondingly) have been applied on biological sequences, aiming to support sequence matching [15], indexing … These neighbors are represented as connected vertices in the text graph. … Related articles All 5 versions

Visualization of Explanations in Recommender Systems MZ Al-Taie, S Kadry – Journal of Advanced Management Science Vol, 2014 – joams.com … We will learn what modalities (Eg text, graphs, tables, and images) can better present explanations to users, through the review of a selection … The text-based format incorporates the use of a number of sentences, with the use of natural language in order to increase transparency … Related articles

Concept Map Based Semantic Representation and Knowledge Visualization J Zeng – Proceedings of the International Conference on …, 2014 – world-comp.org … Besides the above four typical relations, predications are flexibly used to define the relations between concepts. Concept-predication-concept forms a proposition, which is close to natural language expression. … content-type={text, graph, image, sound, video, complex-media} … Related articles All 2 versions

Information Retrieval System Using Vector Space Model for Document Summarization VA Chavan, SR Durugkar – 2014 – ijcseonline.org … Automatic document summarization is an important research area in natural language processing (NLP … summarization since they do not only rely on the local context of a text unit (vertex), however it takes the information recursively drawn from the entire text (graph) into account … Related articles All 2 versions

A Mixed-Initiative Approach for Summarizing Discussions Coupled with Sentimental Analysis N Lalithamani, R Sukumaran, K Alagammai… – Proceedings of the …, 2014 – dl.acm.org … In contr abstractive methods build an internal semantic representat and then use Natural Language Generation Techniques to cre a … the Cluster CMRW (Cluster Conditional Markov Random Walk) model incorporates cluster-level information into the text graph and manipula … Related articles

Summarization Of Documents Based On Extraction And Ordering N Saxena – ijemt.in … In their Lex Rank algorithm, each sentence defines a node in the text graph. … Sentence ordering, which determines the sequence in which to represent a set of pre-selected sentences, is a critical task both for text summarization and natural language generation. … Related articles

Information Retrieval by Document Re-ranking using Term Association Graph K Veningston, R Shanmugalakshmi – Proceedings of the 2014 …, 2014 – dl.acm.org … together in the link structure. TextRank [30] is a graph-based ranking model for natural language text processing. The algorithm takes into account edge weights while computing the score associated with a vertex in the text graph. … Related articles

Text-Driven Reasoning and Multi-Structured Data Analytics for Business Intelligence L Dey, I Verma – Integration of Data Mining in Business …, 2014 – books.google.com … to analysis of traditional data types like numbers or transactional figures in conjunction with non-numerical data like text, graphs, images etc … Given that any Natural Language discourse is loaded with ambiguities, polymorphisms and uncertain- ties this is not a straightforward task … Related articles All 2 versions

A Novel based Approach to Obtaining the Personal Name Aliases from the Web MSS PRASAD, V SHANKAR – ijcsiet.com … fields. Keywords-Semantic Similarity, Information Retrieval, name disambiguation, Word Sense Disambiguation, Lexico syntactic pattern, Natural Language Processing. 1. Introduction: The information searching about people in the web is one of the most … Related articles All 2 versions

Analytical Study on the Relationship between Discourse Markers and Speaking Fluency of Iranian EFL Students B Sadeghi, MRR Yarandi – International Journal, 2014 – ijlcnet.com … use. Brumfit (1984) feels that fluency is “to be regarded as natural language use. “Richard et al. … Page 13. Sadeghi & Yarandi 113 Graph 2. Descriptive Statistics Concerning the Comparison of Two Groups in Music Conversation Graph … Cited by 1 Related articles All 2 versions

Single Document Keyphrase Extraction Using Label Information S Negi – anthology.aclweb.org … halcea and Tarau, 2004) method – an unsupervised graph-based ranking model for extracting keyphrases and “key” sentences from natural language text. … To identify “central” or “key” text units in this text graph, TextRank runs the PageRank algorithm on this constructed graph. … Related articles All 4 versions

Multi-Document Summarization Based On Sentence Clustering Improved Using Topic Words I Lukmana, D Swanjaya, A Kurniawardhani… – JUTI: Jurnal Ilmiah …, 2014 – juti.if.its.ac.id … An abstractive summarization can produce summaries that are more like what a human might generate but it requires deep natural language processing techniques [1]. Because of simple but … Sentence Information Density (SID) is built according to positional text graph approach … Related articles

Automatic Discovery of Personal Name Aliases from the Web Using Lexical Pattern-Based Approach MTM Marawar, W Deepanker, K Patel – ijecs.in … To select the best aliases among the extracted candidates, we propose numerous ranking scores based upon three approaches: lexical pattern frequency, word co-occurrences in an anchor text graph, and page … Conf. Computational Natural Language Learning (CoNLL ’03), pp … Related articles All 2 versions

Domain Vocabulary for Business Intelligence V Damjanovic, W Behrendt – understander.salzburgresearch.at … IBM Watson contains hundreds of different algorithms that evaluate evidence along different dimensions. It utilizes Natural Language Processing (NLP) technology to interpret the question and extract key elements such as the answer type and relationships between entities. … Related articles

Extracting Aliases of Extracting Aliases of a Given Personal Name Using Given Personal Name Using Snippets MNS Chapke, PK Bharne – sites.ijrit.com … Three different approaches are used to find the correct aliases which are lexical pattern frequency, word co-occurrences in an anchor text graph [2], and page counts on the web. … Conf. Computational Natural Language Learning (CoNLL ’03), pp. 33-40, 2003. … Related articles All 2 versions

Study on Agile Process Methodology and Emergence of Unsupervised Learning to Identify Patterns from Object Oriented System M Narendhar, K Anuradha – ICT and Critical Infrastructure: Proceedings of …, 2014 – Springer … improves the quality and productivity, poses several challenges, requiring various algorithms to effectively mine text, graph from such … Application data mining use the term certain related activities and techniques from machine learning, natural language processing and … Related articles All 3 versions

Mining Semantics Structures from Syntactic Structures in Web Document Corpora H Mousavi, S Gao, D Kerr, M Iseli… – International Journal of …, 2014 – World Scientific … Syntactic exceptions are an essential part of any natural language. … without needing to split general patterns (eg Rule 2), SemScape uses patterns with negative con¯dence to specify exceptions and remove many of the incorrectly generated triples from the Text- Graphs. … Related articles

Business Intelligence & Geo Tracking-A Novel Mining Technique to Identify Alerts and Pattern Analysis MV Kamal, D Vasumathi – Computational and Business …, 2014 – ieeexplore.ieee.org … implementation tools improves software debugging business rules for novel projects and also presents strategies for efficient study text, graph mining. … Text mining is concerned with the task of extracting relevant information from natural language text and to search for interesting …

An Effective Drought Early Warning System for Sub-Saharan Africa: Integrating Modern and Indigenous Approaches M Masinde – Proceedings of the Southern African Institute for …, 2014 – dl.acm.org … Though not implemented, the Framework is designed to support natural language processing to allow for translation of the forecasts into the local languages. Figure 1. ITIKI Architecture (source: [13). 64 Page 6. 3 D M t O i s b t t 4 D 4 T a u f a T F K A w p w f f d ( o … Related articles All 2 versions

Algorithms for Recollection of Search Terms Based on the Wikipedia Category Structure S Vandamme, F De Turck – The Scientific World Journal, 2014 – hindawi.com … Zesch and Gurevych [14] use the category graph for natural language applications, such as determining semantic relatedness … Scopus; T. Zesch and I. Gurevych, “Analysis of the Wikipedia category graph for NLP applications,” in Proceedings of the 2nd Workshop Text Graphs, pp … Related articles All 9 versions

Multi-document summarization via Archetypal Analysis of the content-graph joint model E Canhasi, I Kononenko – Knowledge and information systems, 2014 – Springer … as edge weights. They take into account the global information and recursively calculate the sentence significance from the entire text graph rather than simply relying on unconnected individual sentences. These approaches … Cited by 9 Related articles All 4 versions

Efficient Implementation of Web Search Query Reformulation Using Ant Colony Optimization K Veningston, R Shanmugalakshmi – Big Data Analytics, 2014 – Springer … graph is employed in order to provide query suggestion by assessing the linkage structure of the text graph constructed over a … search contexts, location, intent, synonym, polysemic words, generalized and specialized que- ries, concept matching and natural language queries in … Cited by 1 Related articles All 3 versions

Graph-Based Semi-Supervised Learning A Subramanya, PP Talukdar – Synthesis Lectures on Artificial …, 2014 – morganclaypool.com Page 1. Graph-Based Semi-Supervised Learning Amarnag Subramanya Partha Pratim Talukdar SUBR AMANY A • T AL UK D AR GR AP H-BASE D SE MI-SUP E R VISE D L EAR NING MO R GAN & CL A YPOO L ng SYNTHESIS LECTuRES ON ARTIfICIAL … Cited by 3 Related articles All 4 versions

Graph-based models for multi-document summarization E Canhasi – 2014 – lkm.fri.uni-lj.si … 1 2 3 4 3 1 2 4 Figure 2.2 The seven bridges in Königsberg (schematic and graph). Graphs can be used in modeling many natural language processing applications. … algorithms for natural language processing and information retrieval see [5]. Graphs … Related articles

Identifying Event-Specific Sources from Social Media D Mahata, N Agarwal – Online Social Media Analysis and Visualization, 2014 – Springer … It was further improved for making it sensitive to topic based search [17]. Graph based approaches were used for modeling documents and a set of documents as weighted text graphs, and for computing relative impor- tance of textual units for Natural Language Processing [12]. … Related articles All 3 versions

DICH: A framework for discovering implicit communities hidden in tweets D Peng, X Lei, T Huang – World Wide Web, 2014 – Springer … 4.1 Feature selection In natural language processing, a word is the smallest meaningful unit that can be used inde- pendently [7]. An English sentence is formed with words separated with a space. Thus, it is easy to get the individual words from the sentence. … Related articles

Graph Pattern Mining Techniques to Identify Potential Model Organisms AR Nabhan – 2014 – scholarworks.uvm.edu … cludes three biomedical knowledge resources (Bodenreider 2004): (1) Metathesaurus, (2) Semantic Network, and (3) the SPECIALIST natural language processing tools (Browne et al. … range of learning problems involving various data types (eg, text, graphs, and genome 10 … Related articles All 2 versions

Semantic Analysis for Improved Multi-document Summarization of Text QL Israel – 2014 – idea.library.drexel.edu … 99 Page 8. vii List of Figures Figure 1 A Sub-graph of a Text Graph 19 … Also, the semantic triples clustering used to decompose natural language sentences to their most basic meaning and select the most important sentences added to this improvement. … Cited by 3 Related articles All 2 versions

Namesake alias mining on the Web and its role towards suspect tracking T Anwar, M Abulaish – Information Sciences, 2014 – Elsevier … 18 of them are computed from an anchor text graph mined from webpage anchor texts, four are the different association measures between the real name and a candidate, and the last one is frequency of the lexical patterns used to find the candidate. … Cited by 2 Related articles All 5 versions

Effective multi-modality fusion framework for cross-media topic detection L Chu, Y Zhang, G Li, S Wang, W Zhang, Q Huang – 2014 – ieeexplore.ieee.org … A. The Text Graph LDA-based Text Feature. … LDA is a widely used topic model in natural language processing. It assumes that each document is a mixture of a number of topics and each word is generated from one of the document’s topics. … Related articles

Automated Medical Text Summarisation to Support Evidence-based Medicine A SARKER – science.mq.edu.au … A. Sarker, D. Mollá-Aliod, and C. Paris, “Automatic Prediction of Evidence-based Recom- mendations via Sentence-level Polarity Classification,” in Proceedings of the 6th Interna- tional Joint Conference on Natural Language Processing (IJCNLP 2013), (Nagoya, Japan), 2013. … Related articles

Graph-based models for multi-document summarization A ????? Ercan Canhasi ?? T?? F????? C????? I????? S … Related articles

Understanding preferences and similarities from user-authored text: applications to search and recommendations G Ganu – 2014 – rucore.libraries.rutgers.edu Page 1. UNDERSTANDING PREFERENCES AND SIMILARITIES FROM USER-AUTHORED TEXT: APPLICATIONS TO SEARCH AND RECOMMENDATIONS by GAYATREE GANU A dissertation submitted to the Graduate School—New Brunswick … Related articles All 2 versions

[BOOK] Mining user generated content MF Moens, J Li, TS Chua – 2014 – books.google.com Page 1. Chapman & Hall/CRC Social Media and Social Computing Series MINING USER GENERATED CONTENT Edited by Marie-Francine Moens JuanziLi Tat-Seng Chua Q” E?m ‘ CHAPMAN : Page 2. MINING USER GENERATED CONTENT Page 3. … Cited by 12 Related articles All 4 versions

Biomedical Information Extraction: Mining Disease Associated Genes from Literature Z Huang – 2014 – idea.library.drexel.edu … In the proposed integrated approach, concepts extracted from the disease focused literature will be semantically filtered, normalized, and used to construct text graph by … language processing (NLP), information retrieval (IR), and knowledge management are also … Related articles All 3 versions

[BOOK] Computer Engineering: A DEC View of Hardware Systems Design CG Bell, JC Mudge, JE McNamara – 2014 – books.google.com Page 1. COMPUTER ENG|N|EERING Ell LL J. CRAIG MUDGE JOHN E. McNAMARA Page 2. COMPUTER ENG|N| E ERNG A DEC VIEW OF HARDWARE SYSTEMS DESIGN C. GORDON BELL J. CRAIG MUDGE: JOHN E. McNAMARA DIGITAL PRESS Page 3. … Cited by 119 Related articles All 6 versions

Interpreting Document Collections with Topic Models N Aletras – 2014 – etheses.whiterose.ac.uk … brilliant researchers that helped me broaden my research interests. I would also like to thank all of my colleagues in the Natural Language Pro- cessing group for making such a nice working environment. I really appreciated … 66 5.1.3 Creating a Text Graph . . . . . … Related articles All 6 versions

Characteristic times of biased random walks on complex networks M Bonaventura, V Nicosia, V Latora – Physical Review E, 2014 – APS Page 1. PHYSICAL REVIEW E 89, 012803 (2014) Characteristic times of biased random walks on complex networks Moreno Bonaventura,1,2 Vincenzo Nicosia,1 and Vito Latora1,3 1School of Mathematical Sciences, Queen … Cited by 8 Related articles All 8 versions

Handbook of BigDataBench (Version 3.1)—A Big Data Benchmark Suite C Luo, W Gao, Z Jia, R Han, J Li, X Lin, L Wang, Y Zhu… – prof.ict.ac.cn … workloads and data sets in each domain from two perspectives: diverse data models of different types, ie, structured, semi-structured, and unstructured, and different semantics, eg, text, graph, multimedia data … When describing the workloads, we use natural language in English. … Cited by 1 Related articles All 2 versions

The Arev System: Problems Of Design And Implementation For Persons With Impaired Vision A Kuchukyan, S Karapetyan – Middlesex University Research Repository – eprints.mdx.ac.uk Page 37. THE AREV SYSTEM: PROBLEMS OF DESIGN AND IMPLEMENTATION FOR PERSONS WITH IMPAIRED VISION A. Kuchukyan, S. Karapetyan Yerevan Computer Research and Development Institute Yerevan, Armenia … Related articles All 2 versions

A transdisciplinary study of embodiment in HCI, AI and New Media. HDA Al-Shihi – 2014 – bradscholars.brad.ac.uk Page 1. ATRANSDISCIPLINARY STUDY OF EMBODIMENT IN HCI, AI AND NEW MEDIA HDA AL-SHIHI PhD UNIVERSITY OF BRADFORD 2012 Page 2. ATRANSDISCIPLINARY STUDY OF EMBODIMENT IN HCI, AI AND NEW MEDIA Hamda Darwish Ali AL-SHIHI … Related articles All 4 versions

[BOOK] The Analytics Revolution: How to Improve Your Business By Making Analytics Operational In The Big Data Era B Franks – 2014 – books.google.com Page 1. Additional praise for The Analytics Revolution: “I have known Bill for many years and I admire him for his very pragmatic and straight forward approach to operationalizing analyt- ics. Two decades of real-life, hands-on … Cited by 1 All 3 versions

Computational Prediction of Gene Functions through Machine Learning methods and Multiple Validation Procedures D Chicco – 2014 – politesi.polimi.it … relationship between documents related to different biomolecular entities. These approaches can use techniques of Indexing, Text Mining or Natural Language Processing (NLP). Indexing methods (like [82] and [83]) aim at … Related articles All 2 versions