Notes:
JoBimText is an open source framework for the application of distributional semantics using lexicalized features. Distributional semantics is a branch of natural language processing that focuses on the relationship between words and their meanings, and is based on the idea that words that occur in similar contexts have similar meanings. In JoBimText, lexicalized features are used to represent the meaning of words, and are derived from the context in which the words appear.
The JoBimText framework provides a set of tools and algorithms for extracting and representing lexicalized features from text data, and for applying distributional semantics methods to natural language processing tasks. This includes tools for constructing distributional semantic models, for measuring the similarity between words and phrases, and for performing semantic similarity tasks such as word sense disambiguation and relatedness measurement.
Resources:
Wikipedia:
See also:
100 Best Word Embedding Videos | 100 Best Word2vec Videos | Distributional Semantics 2017 | Word2vec & Dialog Systems 2016
JoBimText visualizer: a graph-based approach to contextualizing distributional similarity
C Biemann, B Coppola, MR Glass, A Gliozzo… – … of TextGraphs-8 Graph …, 2013 – aclweb.org
Abstract We introduce an interactive visualization component for the JoBimText project. JoBim-Text is an open source platform for large-scale distributional semantics based on graph representations. First we describe the underlying technology for computing a
Linked disambiguated distributional semantic networks
S Faralli, A Panchenko, C Biemann… – International Semantic …, 2016 – Springer
… 2.1 Learning a JoBimText Model. Following [2], we apply a holing operation where each observation in the text is split into a term and its context. The … The resulting structure is called the JoBimText model [22] of the corpus. A …
word2vec or JoBimText?: A Comparison for Lexical Expansion of Hindi Words
N Ramrakhiyani, S Pawar, G Palshikar – … of the 7th Forum for Information …, 2015 – dl.acm.org
Abstract Exploration of distributional semantics for NLP tasks in Indian languages has been scarce. This work carries out a comparative analysis of two recent and high performing distributional semantics techniques namely word2vec and JoBimText. The task of lexical
Scoring disease-Medication associations using advanced NLP, machine learning, and multiple content sources
B Dandala, M Devarakonda, M Bornea… – Proceedings of the Fifth …, 2016 – aclweb.org
… Distributional Semantics (DS) Type Features. DRE features also include types induced by distribu- tional semantics using the text corpora for the arguments, and the distributional semantics tool used here is called JoBimText [11], which is an open source project …
Unsupervised Conceptualization and Semantic Text Indexing for Information Extraction
E Ruppert – International Semantic Web Conference, 2016 – Springer
… Therefore, we are going to use the JoBimText framework [5] to create symbolic conceptualizations … We are going to create JoBimText models [30] and extend those to interconnected graphs, where we introduce new semantic relations between the nodes …
Jobimviz: A web-based visualization for graph-based distributional semantic models
E Ruppert, M Kaufmann, M Riedl… – Proceedings of ACL …, 2015 – aclweb.org
… 3 Computation of distributional models The visualization is based on distributional mod- els computed with the JoBimText framework (Bie- mann and Riedl, 2013)7; however it can also be used for other semantic models of similar struc- ture …
The ContrastMedium algorithm: taxonomy induction from noisy knowledge graphs with just a few links
S Faralli, A Panchenko, C Biemann, SP Ponzetto – 2017 – ub-madoc.bib.uni-mannheim.de
… (2016)1, which are built in three steps: 1) Learning a JoBimText model … JoBimText models provide sense distinctions that are only partially disambiguated: the list of similar and hy- pernyms terms of each sense, in fact, does not carry sense information …
Do supervised distributional methods really learn lexical inference relations?
O Levy, S Remus, C Biemann, I Dagan – … of the 2015 Conference of the …, 2015 – aclweb.org
… overlap. iments by applying the JoBimText framework4 for scalable distributional thesauri (Biemann and Riedl, 2013) using Google’s syntactic N-grams (Goldberg and Orwant, 2013) as a corpus … discarded. 4http://jobimtext.org …
Distributed Distributional Similarities of Google Books over the Centuries.
M Riedl, R Steuer, C Biemann – LREC, 2014 – pdfs.semanticscholar.org
… 1sf.net/p/jobimtext/wiki/LREC2014_Google_ DT/ 2ASL 2.0, sf.net/projects/jobimtext/ 3http://hadoop.apache.org/ 4https://pig.apache.org … Journal of Language Modelling, 1(1):55–95. 7sf.net/p/jobimtext/wiki/LREC2014_Google_ DT/, http://www.lt.informatik.tu-darmstadt …
Unsupervised, knowledge-free, and interpretable word sense disambiguation
A Panchenko, F Marten, E Ruppert, S Faralli… – arXiv preprint arXiv …, 2017 – arxiv.org
… Instead, these are induced from the input text corpus using the JoBimText approach (Biemann and Riedl, 2013) implemented using the Apache Spark framework4, enabling seamless processing of large text collections. Induction of a WSD model consists of several steps …
Making sense of word embeddings
M Pelevina, N Arefyev, C Biemann… – arXiv preprint arXiv …, 2017 – arxiv.org
… This graph is computed either based on word embeddings learned during the previous step or using semantic similarities provided by the JoBimText framework (Biemann and Riedl, 2013). Similarities using word2vec (w2v) … Similarities using JoBimText (JBT) …
Proceedings of TextGraphs-8 Graph-based Methods for Natural Language Processing
Z Kozareva, I Matveeva, G Melli… – Proceedings of TextGraphs …, 2013 – aclweb.org
… 1 JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity Chris Biemann, Bonaventura Coppola, Michael R. Glass, Alfio Gliozzo, Matthew Hatem and Martin Riedl …
Unsupervised does not mean uninterpretable: The case for word sense induction and disambiguation
A Panchenko, E Ruppert, S Faralli… – Proceedings of the 15th …, 2017 – aclweb.org
… The goal of this step is to build a graph of word similarities, such as (table, chair, 0.78). We used the JoBimText framework (Biemann and Riedl, 88 Page 4. Training Corpus Contexts … 2Select the “JoBimViz” demo and then the “Stanford (En- glish)” model: http://www.jobimtext.org …
Noun sense induction and disambiguation using graph-based distributional semantics
A Panchenko, J Simon, M Riedl… – Proceedings of the 13th …, 2016 – academia.edu
… semantically similar words. To learn sense inventories, we rely on the JoBimText frame- work and distributional semantics (Biemann and Riedl, 2013), adding a word sense disambiguation functionality on the top of it. The key …
There’s no’Count or Predict’but task-based\\selection for distributional models
M Riedl, C Biemann – IWCS 2017—12th International Conference on …, 2017 – aclweb.org
… Abstract In this paper, we investigate the differences between prediction-based (word2vec), dense count- based (GloVe) and sparse count-based (JoBimText) semantic models … This representation is learned using matrix factorization methods. JoBimText (JBT) …
Watsonsim: Overview of a question answering engine
S Gallagher, W Zadrozny, W Shalaby… – arXiv preprint arXiv …, 2014 – arxiv.org
… Several projects have previously explored knowledge management through distributional semantic models, such as JoBimText which may be an excellent candidate for inclusion [1]. Word2Vec, a similar project uses distributional semantics to model relations between phrases …
Ambient Search: A Document Retrieval System for Speech Streams
B Milde, J Wacker, S Radomski, M Mühlhäuser… – … of COLING 2016, the …, 2016 – aclweb.org
… DRUID is implemented as a JoBimText (Biemann and Riedl, 2013) component, which can be down … 2084 Page 4. loaded from the JoBimText project website7 alongside precomputed dictionaries for English. 3.3 Term Ranking …
Impact of MWE resources on multiword recognition
M Riedl, C Biemann – Proceedings of the 12th Workshop on Multiword …, 2016 – aclweb.org
… 2http://jobimtext.org/jobimtext/ components/DRUID/ 3http://www.chokkan.org/software/ crfsuite 4We use the version 1.6 available from: https:// opennlp.apache.org. 5An implementation of the complete system is available at http://maggie.lt.informatik …
Demonstrating Ambient Search: Implicit Document Retrieval for Speech Streams
B Milde, J Wacker, S Radomski, M Mühlhäuser… – … of COLING 2016, the …, 2016 – aclweb.org
… DRUID is a state-of-the-art unsupervised measure for multiword expressions (MWEs) using distributional semantics and precomputed dictionaries for English can be downloaded from the JoBimText project website2 … 2 jobimtext.org/components/druid …
The Gavagai living lexicon
M Sahlgren, AC Gyllensten, F Espinoza… – Language Resources …, 2016 – diva-portal.org
… There are also several academic projects that pro- vide data-driven thesauri, like the Wortschatz project,3 and the JoBimText project.4 This paper presents a continuously learning distributional thesaurus — the Gavagai Living Lexicon — that updates its semantic model …
Vectors or Graphs? On Differences of Representations for Distributional Semantic Models
C Biemann – Proceedings of the 5th Workshop on Cognitive Aspects …, 2016 – aclweb.org
… The JoBimText (Biemann and Riedl, 2013) framework is a scalable graph-based DSM implementation, developed in cooperation with IBM Research (Gliozzo et al., 2013) … Using the JoBimText DSM as a core, we extend this model in several ways …
Unsupervised relation extraction of in-domain data from focused crawls
S Remus – Proceedings of the Student Research Workshop at the …, 2014 – aclweb.org
… By using the JoBimText framework, we ac- cept their theory, which states that dimensionality- reduced vector space models are not expressive enough to capture the full semantics of words, phrases, sentences, documents or relations …
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LT Home, C Biemann… – … of the 8th …, 2013 – lt.informatik.tu-darmstadt.de
#Information about the Technische Universität Darmstadt.
Mobile context recommendations from social media through geotopical clustering
E Williams, J Gray, B Dixon – … of Alabama, Tech …, 2016 – eawilliams2.students.cs.ua.edu
… For each keyword in the comma-separated input list, we pass the keyword to the JoBimText distributional semantics framework, described in [9]. The JoBimText framework receives a corpus of text and analyzes the … JoBimText extracts pairs of …
BISHOP-Big Data Driven Self-Learning Support for High-performance Ontology Population.
D Knoell, M Atzmueller, C Rieder, KP Scherer – LWDA, 2016 – kde.cs.uni-kassel.de
… A possible application for this task could be “JoBimText” [15]. A further description is given in section 2.3 … There are approaches like “JoBimText” [15] which can calculate a thesaurus out of huge corpora, but do not take advantage of the structure of the documents …
Running into Brick Walls Attempting to Improve a Simple Unsupervised Parser
M Riedl, T Feuerbach, C Biemann – Bochumer Linguistische …, 2016 – academia.edu
… For German and Portuguese we only observe improvements when using universal 5The implementation is available under the Apache 2.0 license: http://jobimtext. org/jobimtext/ /components/unsupervised-parser 6Although …
Narrowing the loop: integration of resources and linguistic dataset development with interactive machine learning
SM Yimam – Proceedings of the 2015 Conference of the North …, 2015 – aclweb.org
… We have used WordNet, PPDB, and JobimText DT3 to provide paraphrase 3http://goo.gl/0Z2Rcs Figure 3: Amharic POS tagging … setups Baseline top 1 top 5 top 10 WordNet 59.0 60.3 61.4 61.9 ppdb 59.0 60.2 62.2 64.6 JoBimText 59.0 59.9 60.3 60.4 2in3 59.0 60.7 65.3 66.2 …
Learning Paraphrasing for Multi-word Expressions
SM Yimam, HM Alonso, M Riedl… – MWE 2016-Multiword …, 2016 – hal.inria.fr
… the candidates match. To satisfy condition b), we have used the JoBimText DT database API (Ruppert et al., 2015) to obtain single word candidates with multiple senses according to automatic sense in- duction. We conduct …
GermEval 2015: LexSub–A shared task for German-language lexical substitution
T Miller, D Benikova, S Abualhaija – Proceedings of GermEval, 2015 – academia.edu
… The linked resources include GermaNet 9.0, WordNet 3.0, and the English and German versions of Wikipedia and Wik- tionary. JoBimText (Biemann and Riedl, 2013) is an au- tomatically induced resource for German by means of distributional semantics …
Simulating ibm watson in the classroom
WW Zadrozny, S Gallagher, W Shalaby… – Proceedings of the 46th …, 2015 – dl.acm.org
… To give some examples, available projects which would complement text analytics projects such as ours could include JoBimText since it has a unique distributional se- mantic approach to knowledge management [4] or Word2Vec (to assist for measuring relationships between …
Using pseudowords for algorithm comparison: an evaluation framework for graph-based word sense induction
FM Cecchini, M Riedl, C Biemann – … of the 21st Nordic Conference on …, 2017 – ep.liu.se
… Both kinds of ego word graphs will be induced by the distributional thesauri com- puted on a corpus consisting of 105 million En- glish newspaper sentences3, using the JoBimText (Biemann and Riedl, 2013) implementation …
Scaling to large3 data: An efficient and effective method to compute distributional thesauri
M Riedl, C Biemann – Proceedings of the 2013 Conference on Empirical …, 2013 – aclweb.org
… Especially, we shed light on the interaction of similarity measures and corpus size, as well as aspects of scalability. We shortly introduce the JoBimText framework for distributional semantics and show its scalability for large corpora … 3https://sf.net/projects/jobimtext/ 888 Page 6 …
A framework for enriching lexical semantic resources with distributional semantics
C Biemann, S Faralli, A Panchenko… – Natural Language …, 2018 – cambridge.org
… from a text corpus. To this end, we first create a sense inventory from a large text collection using graph- based word sense induction as provided by the JoBimText project (Biemann and Riedl 2013). The resulting structure contains …
Distributional semantics for resolving bridging mentions
T Feuerbach, M Riedl, C Biemann – Proceedings of the International …, 2015 – aclweb.org
… net/projects/jobimtext/files/data/ models/en_news120M_stanford_lemma/ 2Our definition is based on quasi-bridges from the Berke- ley System’s source code (Durrett and Klein, 2013) … JoBimText Visualizer: A graph- based approach to contextualizing distributional similarity …
Evaluating Distributional Semantic Models with Russian Noun-Adjective Compositions
P Panicheva, E Protopopova, G Bukia… – … Conference on Analysis …, 2016 – Springer
… Language Technology Group (Ch. Biemann and colleagues, Technical University of Darmstadt, Germany). JoBimText 3 is a web application which processes corpora in German, English and Russian. The toolkit provides automatic …
Towards a resource based on users’ knowledge to overcome the Tip of the Tongue problem.
M Zock, C Biemann – Proceedings of the 5th Workshop on Cognitive …, 2016 – aclweb.org
… Word Similarity: We used the JoBimText distributional semantic model, its similarity score being based on common dependency parse contexts, which requires a language-specific parser … 9 Available at www.jobimtext.org 10 Available at http://corpora.informatik.uni-leipzig.de …
Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl
A Panchenko, E Ruppert, S Faralli, SP Ponzetto… – arXiv preprint arXiv …, 2017 – arxiv.org
… Nutch) Linguistic Analysis: lefex (Apache Hadoop) WARC web crawls Filtered preprocessed documents §3.1 §3.2 §3.3 Comp. of Distributional Model: JoBimText (Apache Spark) §4.2 Term Vectors, Distributional Thesaurus POS …
GermaNER: Free Open German Named Entity Recognition Tool
DBSMY Prabhakaran, SC Biemann – pdfs.semanticscholar.org
… 6.5 Topic Clusters Inspired by the semantic clusters of the ExB system, we have applied LDA topic modelling5 to above-mentioned JoBimText German distribu- tional thesaurus, using the thesaurus entries as ‘documents’ for LDA …
Matching, Reranking and Scoring: Learning Textual Similarity by Incorporating Dependency Graph Alignment and Coverage Features
S Kohail, C Biemann – 18th International Conference on …, 2017 – inf.uni-hamburg.de
… By manual inspection, ?, ? and ? are set to 10, 5 and 2 respectively. For lexical expansions features, we obtain the top 10 DT expansions using the JoBimText API5 … We choose the model which provides 5 www.jobimtext.org/jobimviz-web-demo/api-and-demo-documentation …
Evaluating GeoContext: A system for creating geographical topics from a social media stream
E Williams, J Gray, B Dixon – … Computing, Electronics & Mobile …, 2016 – ieeexplore.ieee.org
… Both parameters filter the stream of tweets that are located within the given coordinates or contain the given keywords, respectively. GeoContext utilizes JoBimText [6], a distributional semantics framework, in order to expand the specified keywords into a set of related keywords …
Can Network Embedding of Distributional Thesaurus be Combined with Word Vectors for Better Representation?
A Jana, P Goyal – arXiv preprint arXiv:1802.06196, 2018 – arxiv.org
… One such represen- tation is JoBimText proposed by Biemann and Riedl (2013) that contains, for each word, a list of words that are similar with respect to their bi- gram distribution, thus producing a network rep- resentation …
GeoContext: Discovering geographical topics from social media
E Williams – Advances in Social Networks Analysis and Mining …, 2016 – ieeexplore.ieee.org
… IEEE/ACM ASONAM 2016, August 18-21 2016, San Francisco, CA, USA 978-1-5090-2846-7/ 16/$31.00 ©2016 IEEE 1342 Page 2. If keywords are given as input, GeoContext utilizes the JoBimText framework [4] to expand the keywords into a set of related keywords …
Rule-based Dependency Parse Collapsing and Propagation for German and English.
E Ruppert, J Klesy, M Riedl, C Biemann – GSCL, 2015 – hypermedia.ids-mannheim.de
… 1We provide the framework with rulesets for English and German under the permissive ASL 2.0 license at http:// jobimtext.org/dependency-collapsing … 5.3 Similarity Computation The similarity computation is performed using the JoBimText framework (Biemann and Riedl, 2013) …
Analysing domain suitability of a sentiment lexicon by identifying distributionally bipolar words
L Flekova, D Preo?iuc-Pietro, E Ruppert – Proceedings of the 6th …, 2015 – aclweb.org
… lexicon word. Us- ing the JoBimText framework (Biemann and Riedl, 2013), we build a large Twitter bigram thesaurus which serves as a background frequency distribu- tion which aids in ranking the bigrams (see section 3.1). For …
Ranking entities for web queries through text and knowledge
M Schuhmacher, L Dietz… – Proceedings of the 24th …, 2015 – dl.acm.org
… spelling mistakes within queries and documents). GloVe (Glo) / JoBimText (Jo): To generalize across different syn- onyms and word senses, we study the utility of distributional repre- sentations of words. The general idea of these …
Using linked disambiguated distributional networks for word sense disambiguation
A Panchenko, S Faralli, SP Ponzetto… – Proceedings of the 1st …, 2017 – aclweb.org
… Building a Distributional Thesaurus (DT). At this stage, a similarity graph over terms is induced from a corpus, where each entry consists of the most similar 200 terms for a given term using the JoBimText method (Biemann and Riedl, 2013). Word Sense Induction …
A Scalable Framework for Data-Driven Ontology Evaluation.
D Knoell, M Atzmueller, C Rieder, KP Scherer – WM, 2017 – pdfs.semanticscholar.org
… These relations can then form the edges for the graph. To get labels for the edges a semantic analysis of the sentences is needed. This analysis can be done, eg, with a tool like JoBimText [7]. When the attributed graph is built, it can be compared to the ontology …
(German) Language Processing for Lucene
B Entrup – International Conference on Applications of Natural …, 2015 – Springer
… 7. For example, for German http://sourceforge.net/projects/jobimtext/files/data/models/ de_news70M_pruned.zip/download; based on 70 million sentences from a news corpus extracted using the system described in [1]. Notes. Acknowledgemets …
An automatic approach to identify word sense changes in text media across timescales
S Mitra, R Mitra, SK Maity, M Riedl… – Natural Language …, 2015 – cambridge.org
… The edge density inside each of these neighborhoods (n) was set to 200 as well. The parameter for regulating the cluster size was set to option (a) (cf. Section 4) 7 Available for download at http://sourceforge.net/p/jobimtext/wiki/ https://www.cambridge.org/core/terms …
UKP-WSI: UKP lab SemEval-2013 task 11 system description
HP Zorn, I Gurevych – Second Joint Conference on Lexical and …, 2013 – aclweb.org
… For the 5The software used to create the DT is available from http://www.jobimtext. org WP-based runs, the clustering based on PMI pro- duced more clusters and therefore scored higher on the F1 measure than the LLR-based run …
Webkorpora in Computerlinguistik und Sprachforschung Web Corpora for Computational Linguistics
A Mehler – informatik.tu-darmstadt.de
… For a scalable implementation of co-occurrence significance measures and second order similarities, the reader is referred to the JoBimText project [21].23 Figure 3 illustrates the process of annotating and pattern counting using the Hadoop framework: Sentences are tokenized …
Delexicalized supervised German lexical substitution
G Hintz, C Biemann – Proceedings of GermEval, 2015 – sites.google.com
… Quasthoff et al. (2006) and define the fol- lowing features: For a given sentence regarded as a 8https://code.google.com/p/mate-tools/ 9The DTs are available at https://sourceforge. net/projects/jobimtext/files/data/ models/ Page 4 …
Replacing OOV Words For Dependency Parsing With Distributional Semantics
P Kolachina, M Riedl, C Biemann – … of the 21st Nordic Conference on …, 2017 – aclweb.org
… 2http://www.jobimtext.org 3we have tried a few thresholds in preliminary experi- ments and did not find results to be very sensitive in the range of 2 – 20 13 Page 4. respectively the most similar word of those with the longest common suffix. 4.2 Corpora for Similarity Computation …
Discovering geographical topics from social media
E Williams – 2017 – search.proquest.com
… For each. keyword in the comma-separated input list, we pass the keyword to the JoBimText distributional … The. JoBimText framework uses a corpus of text such as Wikipedia and analyzes the structure of the. text through methods such as a dependency parser …
Porting an open information extraction system from english to german
T Falke, G Stanovsky, I Gurevych, I Dagan – Proceedings of the 2016 …, 2016 – aclweb.org
… Following our analysis, we implemented a German version of PropS, named PropsDE. It uses mate- tools for POS tagging, lemmatizing and parsing (Bohnet et al., 2013). Dependencies are collapsed and propagated with JoBimText (Ruppert et al., 2015) …
That’s sick dude!: Automatic identification of word sense change across different timescales
S Mitra, R Mitra, M Riedl, C Biemann… – arXiv preprint arXiv …, 2014 – arxiv.org
… 5.1 Signals of sense change Making comparisons between all the pairs of time periods gave us 28 candidate words lists. For 2data available at http://sf.net/p/jobimtext/ wiki/ LREC2014_Google_DT/ Page 5. Figure 1: Example of the birth of a new sense for the word ‘ …
Combining supervised and unsupervised parsing for distributional similarity
M Riedl, I Alles, C Biemann – Proceedings of COLING 2014, the 25th …, 2014 – aclweb.org
… 4www.jobimtext.org, (Biemann and Riedl, 2013) 1438 Page 5. per term, which defines the similarity between terms. Per term, the most similar terms are subsequently ranked, resulting in a distributional thesaurus as introduced by Lin (1997). 4 Evaluation …
EmpiriST: AIPHES-Robust Tokenization and POS-Tagging for Different Genres
S Remus, G Hintz, C Biemann, CM Meyer… – Proceedings of the 10th …, 2016 – aclweb.org
… ticles. 3. Similar words JoBimText (Biemann and Riedl, 2013) to obtain a distributional the- saurus (DT) from which the four most similar words for the current token are used. The un- derlying motivation is to be able to correctly …
Learning semantic relations with distributional similarity
P Herger – 2014 – lt.informatik.tu-darmstadt.de
Page 1. Department of Software Engineering and Theoretical Computer Science Master’s Thesis Learning semantic relations with distributional similarity Priska Herger September 23, 2014 Advisors: Prof. Dr. Chris Biemann …
Amy Woolf at
PD Form – academia.edu
Page 1. Proof Delivery Form Natural Language Engineering Date of delivery: Journal and vol/article ref: NLE 1500011 Number of pages (not including this page): 26 This proof is sent to you on behalf of Cambridge University Press …
Supervised all-words lexical substitution using delexicalized features
G Szarvas, C Biemann, I Gurevych – … of the 2013 Conference of the …, 2013 – aclweb.org
… 5http://corpora.informatik.uni-leipzig.de/ 6open source implementation and data available at http://sourceforge.net/p/jobimtext 7The pruning operation greatly reduces runtime at the- saurus collection, rendering memory reduction techniques like (Charikar et al., 2004) as …
Semantic Feature Aggregation for Gender Identification in Russian Facebook
P Panicheva, A Mirzagitova, Y Ledovaya – Conference on Artificial …, 2017 – Springer
… the answer is in your facebook likes. arXiv preprint arXiv:1703.07726 (2017). 10. Gliozzo, A., Biemann, C., Riedl, M., Coppola, B., Glass, MR, Hatem, M.: Jobimtext visualizer: a graph-based approach to contextualizing distributional similarity …
Text: Now in 2D! a framework for lexical expansion with contextual similarity
C Biemann, M Riedl – Journal of Language Modelling, 2013 – jlm.ipipan.waw.pl
… {heat, weather, temperature, rain, flue, wind, chill, disease}. In Figure 3, the scores per pair are listed: eg the pair <heat,(dobj;caught;@)> 5 http://sourceforge.net/p/ jobimtext/wiki/Home/ [ 69 ] Page 16. Chris Biemann, Martin Riedl …
SemRelData?Multilingual Contextual Annotation of Semantic Relations between Nominals: Dataset and Guidelines.
D Benikova, C Biemann – LREC, 2016 – lrec-conf.org
… Zhekova (2011). The implementation of JoBimText15 (Biemann and Riedl, 2013) of those patterns was applied to the English source texts that were annotated for Sem- 15http://www.jobimtext.org 4158 Page 6. RelData. As the …
Natural language processing: Integration of automatic and manual analysis
R Eckart de Castilho – 2014 – tuprints.ulb.tu-darmstadt.de
Page 1. Natural Language Processing: Integration of Automatic and Manual Analysis Natürliche Sprachverarbeitung: Integration automatischer und manueller Analyse Zur Erlangung des akademischen Grades Doktor-Ingenieur …
Natural language processing: Integration of automatic and manual analysis
RE de Castilho – 2014 – d-nb.info
Page 1. Natural Language Processing: Integration of Automatic and Manual Analysis Natürliche Sprachverarbeitung: Integration automatischer und manueller Analyse Zur Erlangung des akademischen Grades Doktor-Ingenieur …
Knowledge Graph Entity Representation and Retrieval
A Kotov – tutorial chapter, RuSSIR, 2016 – cs.wayne.edu
Page 1. Knowledge Graph Entity Representation and Retrieval Alexander Kotov Wayne State University, Detroit, USA kotov@wayne.edu Abstract. Recent studies indicate that nearly 75% of queries issued to Web search engines …
Natural Language Processing: Integration of Automatic and Manual Analysis
N Sprachverarbeitung – pdfs.semanticscholar.org
Page 1. Natural Language Processing: Integration of Automatic and Manual Analysis Natürliche Sprachverarbeitung: Integration automatischer und manueller Analyse Zur Erlangung des akademischen Grades Doktor-Ingenieur …
Distributed language representation for authorship attribution
M Kocher, J Savoy – Digital Scholarship in the Humanities, 2017 – academic.oup.com
Abstract. Distributed language representation (deep learning) has been applied successfully in different applications in natural language processing. Using thi.
SKIMMR: Facilitating knowledge discovery in life sciences by machine-aided skim reading
V Nová?ek, GAPC Burns – PeerJ, 2014 – peerj.com
Background. Unlike full reading, ‘skim-reading’ involves the process of looking quickly over information in an attempt to cover more material whilst still being able to retain a superficial view of the underlying content. Within this work, we specifically emulate this natural human activity …