Notes:
Deep natural language processing (Deep NLP) is a subfield of artificial intelligence and natural language processing that involves the use of deep learning techniques to analyze and interpret human language. Deep learning is a type of machine learning that involves the use of artificial neural networks to learn patterns and relationships in data. In the context of natural language processing, deep learning techniques can be used to analyze and interpret language at a deeper, more nuanced level, allowing computers to better understand and respond to human language.
Deep NLP is often used in intelligent tutoring systems to help the system understand and interpret student responses and questions, and to provide personalized feedback and guidance. For example, an intelligent tutoring system might use Deep NLP techniques to analyze a student’s written responses to prompts or questions, and to provide feedback on grammar, spelling, and other language-related issues. The system might also use Deep NLP to understand and interpret more complex language phenomena, such as idioms, metaphors, and other figurative language, which can be difficult for traditional natural language processing systems to understand.
In addition to providing feedback and guidance, Deep NLP can also be used in intelligent tutoring systems to personalize the learning experience for individual students. For example, the system might use Deep NLP to analyze a student’s language use and style, and to adapt the content and delivery of the material to better match the student’s needs and preferences. This can help to improve the effectiveness of the tutoring and make the learning experience more engaging and enjoyable for the student.
Resources:
See also:
Alchemy Open Source AI | DeepDive | EntityCube | YAGO-QA | YAGO2
An Overview of Shallow and Deep Natural Language Processing for Ontology Learning A Zouaq – Ontology Learning and Knowledge Discovery Using …, 2011 – igi-global.com Abstract This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques for knowledge extraction from text, namely shallow techniques and deep techniques, and explains their … Cited by 6 Related articles All 2 versions
Automatic Short Essay Scoring Using Natural Language Processing to Extract Semantic Information in the Form of Propositions D Kerr, H Mousavi, M Iseli – CRESST Report, 2013 – semscape.cs.ucla.edu … In this paper, we introduce a novel technique for using domain-independent, deep natural language processing techniques to automatically extract meaning from student essays in the form of propositions and match the extracted propositions to the expected response. … Cited by 1 Related articles
Supporting Agile Software Development by Natural Language Processing B Plank, T Sauer, I Schaefer – … Eternal Systems via Evolving Software, Data …, 2013 – Springer … Alternatively, deep natural language processing might be applied to gather structured objects. For instance, the example user story could be represent as shown in Figure 7, where natural language parsing and argument classifica- tion has been applied. … Related articles All 4 versions
Deep Natural Language Processing for Italian Sign Language Translation A Mazzei, L Lesmo, C Battaglino, M Vendrame… – AI* IA 2013: Advances in …, 2013 – Springer Abstract This paper presents the architecture of a translator from written Italian into Italian Sign Language. We describe the main features of the four modules of this architecture, ie a dependency parser for Italian, an ontology based semantic interpreter, a generator based … Related articles All 2 versions
Generating Description Logic {\ mathcal ALC} from Text in Natural Language RR de Azevedo, F Freitas, R Rocha… – … of Intelligent Systems, 2014 – Springer … AKA Verlag / IOS Press (2009) ISBN: 978-3-89838-621-0 11. Zouaq, A.: An Overview of Shallow and Deep Natural Language Processing for Ontology Learning. In: Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances, vol. 2, pp. … Related articles
A study on plagiarism detection and plagiarism direction identification using natural language processing techniques MYM Chong – 2013 – wlv.openrepository.com Page 1. A Study on Plagiarism Detection and Plagiarism Direction Identification Using Natural Language Processing Techniques Man Yan Miranda Chong A thesis submitted in partial fulfilment of the requirements of the University of … Cited by 1 Related articles All 6 versions
An Approach for Learning and Construction of Expressive Ontology from Text in Natural Language RRD Azevedo, F Freitas, RGC Rocha… – Web Intelligence (WI …, 2014 – ieeexplore.ieee.org Page 1. An Approach for Learning and Construction of Expressive Ontology from Text in Natural Language Ryan Ribeiro de Azevedo, Fred Freitas, Rodrigo G. C. Rocha Computer Science, UAG/Federal Rural University of Pernambuco … Cited by 1
An Approach for Automatic Expressive Ontology Construction from Natural Language RR de Azevedo, F Freitas, R Rocha… – … Science and Its …, 2014 – Springer … LNCS, vol. 4519, pp. 670–685. Springer, Heidelberg (2007) 17. Zouaq, A.: An Overview of Shallow and Deep Natural Language Processing for Ontology Learning. In: Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances. ch. 2, pp. … Cited by 1
Towards an OWL-based framework for extracting information from clinical texts N Blaylock, W de Beaumont, J Allen… – Proceedings of the 2nd …, 2011 – dl.acm.org … [12] M. Swift, N. Blaylock, J. Allen, W. de Beaumont, L. Galescu, and H. Jung. Augmenting a deep natural language processing system with UMLS. In Proceedings of the Fourth Symposium on Semantic Mining in Biomedicine (SMBM 2010), Hinxton, UK, October 2010. … Cited by 1 Related articles All 5 versions
Improved head-driven statistical models for natural language parsing L Yuan – Journal of Central South University, 2013 – Springer … Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling (SRL) is very necessary for deep natural language processing. … Related articles All 4 versions
Representing Knowledge in DL< i> ALC from Text RR de Azevedo, F Freitas, R Rocha… – Procedia Computer …, 2014 – Elsevier … 670-685. Springer, June 2007. [17]; Zouaq, A. : An Overview of Shallow and Deep Natural Language Processing for Ontology Learning. Chapter 2. Pg 16-37. In: Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances. IGI Global. EUA . …
Recent Advances in Conversational Intelligent Tutoring Systems. V Rus, SK D’Mello, X Hu, AC Graesser – AI magazine, 2013 – questia.com … Another authoring tool, called SEMILAR (derived from semantic similarity toolkit; Rus et al. [2013]), is being developed as well to assist with authoring algorithms for deep natural language processing of student input in conversational ITSs. (3). … Cited by 11 Related articles All 5 versions
Exploiting semantic roles for asynchronous question answering in an educational setting D Wen, J Cuzzola, L Brown – Advances in Artificial Intelligence, 2012 – Springer … Abstract. Recent question answering (QA) research has started to in- corporate deep natural language processing (NLP) such as syntactic and semantic parsing in order to enhance the capability of selecting the most relevant answers to a given question. … Cited by 2 Related articles All 3 versions
[BOOK] Advances in deep parsing of scholarly paper content U Schäfer, B Kiefer – 2011 – Springer … Heart of Gold is an XML-based middleware architecture for the integration of multilingual shallow and deep natural language processing components, developed under the umbrella of the DELPH-IN initiative4. The employed Heart of Gold configuration instance starts with a … Cited by 7 Related articles All 7 versions
Progressions (LPs) in DeepTutor V Rus, W Baggett, E Gire, D Franceschetti… – … Systems: Volume 1- …, 2013 – books.google.com … An authoring tool that allows us to explore and design algorithms for deep natural language processing has been developed (for more information about the Semantic Similarity, or simply SEMILAR, toolkit, see www. semanticsimilarity. org). …
Towards Learner Models based on Learning Progressions (LPs) in DeepTutor V Rus, W Baggett, E Gire, D Franceschetti… – … for Intelligent Tutoring …, 2013 – gifttutoring.org … An authoring tool that allows us to explore and design algorithms for deep natural language processing has been developed (for more information about the Semantic Similarity, or simply SEMILAR, toolkit, see www. semanticsimilarity. org). … Related articles All 7 versions
A corpus of clinical narratives annotated with temporal information L Galescu, N Blaylock – Proceedings of the 2nd ACM SIGHIT …, 2012 – dl.acm.org … We are working to- wards applying deep Natural Language Processing tools to- wards understanding such narratives. This requires both the extraction and classification of the relevant events, and the placing of those events in time, or at least in relation to one another. … Cited by 9 Related articles All 13 versions
Why we need evolutionary semantics L Steels – KI 2011: Advances in Artificial Intelligence, 2011 – Springer … This approach stands in contrast to the one explored in earlier deep natural language processing research which used sophisticated grammars based on linguistic the- ory and procedural semantics for the precise interpretation of meaning in terms of world models derived from … Cited by 1 Related articles All 8 versions
Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites P Sondhi, CX Zhai – Proceedings of the 23rd ACM International …, 2014 – dl.acm.org … How- ever most of these approaches are designed to answer only a restricted set of questions such as short and precise fac- toid [3] or definitional [5]. In addition they tend to require deep natural language processing steps such as generation of parse trees to analyze the …
Textual evidence gathering and analysis JW Murdock, J Fan, A Lally, H Shima… – IBM Journal of …, 2012 – ieeexplore.ieee.org Page 1. Textual evidence gathering and analysis JW Murdock J. Fan A. Lally H. Shima BK Boguraev One useful source of evidence for evaluating a candidate answer to a question is a passage that contains the candidate answer and is relevant to the question. … Cited by 21 Related articles All 3 versions
Towards a Framework for Ontology Learning from Inter-actions in Natural Language and Reasoning RR de Azevedo, F Freitas, RGC Rocha – 2014 – faculty.uoit.ca Page 1. 1 Towards a Framework for Ontology Learning from Inter- actions in Natural Language and Reasoning Ryan Ribeiro de Azevedo, Fred Freitas, Rodrigo GC Rocha, José Antônio Alvez de Menezes, Cleyton MO Rodrigues …
Instructor-aided asynchronous question answering system for online education and distance learning D Wen, J Cuzzola, L Brown – The International Review of Research in …, 2012 – irrodl.org … However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. … Cited by 1 Related articles All 5 versions
Deep Multi-Instance Transfer Learning D Kotzias, M Denil, P Blunsom, N de Freitas – arXiv preprint arXiv: …, 2014 – arxiv.org … sentences. 2 Background 2.1 Deep Natural Language Processing Following the sweeping success of deep learning in computer vision, researchers in deep learning have begun to focus their efforts on other tasks. In particular …
Evaluating Machine Reading Systems through Comprehension Tests. A Peñas, EH Hovy, P Forner, Á Rodrigo, RFE Sutcliffe… – LREC, 2012 – lrec.elra.info … Background text collections are comparable collections harvested from the web for a set of predefined topics. This approach allows deep natural language processing issues to be investigated in both monolingual and cross-lingual contexts. … Cited by 2 Related articles All 4 versions
Making Watson fast EA Epstein, MI Schor, BS Iyer, A Lally… – IBM Journal of …, 2012 – ieeexplore.ieee.org … This paper describes how a large set of deep natural-language processing programs were integrated into a single application, scaled out across thousands of central processing unit cores, and optimized to run fast enough to compete in live Jeopardy!i games. … Cited by 11 Related articles All 3 versions
Generating Description Logic ALC from Text in Natural RR de Azevedo, F Freitas, R Rocha… – … of Intelligent Systems, 2014 – Springer … AKA Verlag/IOS Press (2009) ISBN: 978-3-89838-621-0 11. Zouaq, A.: An Overview of Shallow and Deep Natural Language Processing for Ontology Learning. In: Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances, vol. 2, pp. … Related articles
Smartphone-Based Self Management System for Type-2 Diabetes Patients. E Aramaki, M Miyabe, K Waki, H Fujita… – AAAI Spring Symposium …, 2012 – aaai.org … In contrast, the other parts are challenging, because it have to handle text data. To realize precise well performance, deep Natural Language Processing (NLP) techniques are required. This paper mainly focuses on the NLP techniques for the proposed system. System … All 2 versions
Full-fledged temporal processing: bridging the gap between deep linguistic processing and temporal extraction F Costa, A Branco – Journal of Language Modelling, 2013 – jlm.ipipan.waw.pl … Deep natural language processing systems have been successfully employed in many applications, like machine translation (Müller and Kasper, 2000; Bond et al., 2005), grammar checking (Bender et al., 2004) and ontology acquisition (Nichols et al., 2006), among others. … Cited by 1 Related articles All 2 versions
Query Rewriting Using Shallow Language Processing: Effects on Keyword Subject Searches A Mastora, S Kapidakis – … on Supporting User’s Exploration on Digital …, 2012 – ixa2.si.ehu.es … phrases. Concerning the language processing of queries, Schafer [6] states that deep natural language processing (DNLP) systems try to apply as much linguistic knowledge as possible to analyse natural language utterance. … Cited by 1 Related articles
Text Summarization in Android Mobile Devices OM Foong, SP Yong, AL Lee – … of the First International Conference on …, 2014 – Springer … produce shorter summarized text. Most researchers applied extractive summary as it is more difficult to develop abstractive summary due to its implementation of deep natural language processing. The main challenge would … Related articles
DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference. F Niu, C Zhang, C Ré, JW Shavlik – VLDS, 2012 – www-cs.stanford.edu … However, DeepDive goes deeper in two ways: (1) Unlike prior large-scale KBC systems, DeepDive performs deep natural language processing (NLP) to extract useful 1http://research.cs.wisc.edu/hazy/deepdive 2http://lemurproject.org/clueweb09.php/ … Cited by 16 Related articles All 13 versions
Organizing information on the web through agreement-conflict relation classification J Mizuno, E Nichols, Y Watanabe, K Inui – Information Retrieval …, 2012 – Springer … The goals of Dispute Finder and our system are similar, but Dispute Finder relies on crowd-sourcing to build its dispute database which limits its automation poten- tial, while we use deep natural language processing technology to automatically identify conflicts. 6 Conclusion … Cited by 1 Related articles All 5 versions
Grounding Language through Evolutionary Language Games L Steels – Language Grounding in Robots, 2012 – Springer … This approach stands in contrast to the one explored in earlier deep natural language processing research which used sophisticated grammars based on linguistic theory and procedural semantics for the precise interpretation of meaning in terms of world models derived from … Cited by 8 Related articles All 6 versions
Selecting answers to questions from Web documents by a robust validation process A Grappy, B Grau, MH Falco, AL Ligozat… – Proceedings of the …, 2011 – dl.acm.org … questions. Best systems make use of deep Natural Language Processing (NLP) techniques, in order to match questions and candidate passages and extract answers [1], [2], [3] for some European languages and [4] for French. … Cited by 12 Related articles All 11 versions
A hybrid machine learning model for multi-document summarization MA Fattah – Applied Intelligence, 2014 – Springer … source. However, abstractive approaches require deep natural language processing techniques such as seman- tic representation, inference, and natural language genera- tion, which have yet to reach a mature stage [40]. … Cited by 2 Related articles All 3 versions
Weighted consensus multi-document summarization D Wang, T Li – Information Processing & Management, 2012 – Elsevier … Abstractive summarization involves information fusion, sentence compression and reformulation (Knight and Marcu, 2002 and Jing and McKeown, 2000). Although an abstractive summary could be more concise, it requires deep natural language processing techniques. … Cited by 6 Related articles All 9 versions
ClausIE: clause-based open information extraction L Del Corro, R Gemulla – … of the 22nd international conference on World …, 2013 – dl.acm.org Page 1. ClausIE: Clause-Based Open Information Extraction Luciano Del Corro Max-Planck-Institute für Informatik Saarbrücken, Germany corogg@mpi-inf.mpg.de Rainer Gemulla Max-Planck-Institute für Informatik Saarbrücken, Germany rgemulla@mpi-inf.mpg.de … Cited by 21 Related articles All 15 versions
User-Centered Maintenance of Concept Hierarchies K Eckert, R Meusel, H Stuckenschmidt – Ontology Learning and …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 1 Related articles All 2 versions
Cross-language ontology learning H Hjelm, M Volk – … Learning and Knowledge Discovery Using the …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 5 Related articles All 2 versions
Mining parallel knowledge from comparable patents B Lu, BK Tsou, T Jiang, J Zhu… – Ontology Learning and …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 3 Related articles All 4 versions
Contextual question answering for the health domain W Wong, J Thangarajah… – Journal of the American …, 2012 – Wiley Online Library … Unlike existing systems that rely on templates and text snippets from web documents to produce answers, enquireMe uses the answer component of question–answer pairs for its “naturalness.” The need for deep natural language processing, which is common in systems such … Cited by 1 Related articles All 7 versions
A better indicator for genre classification: Topic word or surface text feature: A case study of recognition of brief biography W Xiong – … Electronics and Electrical Engineering (ISEEE), 2014 …, 2014 – ieeexplore.ieee.org … in previous literature. As is mentioned above, a deep natural language processing technique is not suitable for online real-time intelligent text processing, due to poor precision and awkward response time. Some researchers …
Tuple refinement method based on relationship keyword extension X Yang, J Yang, C Chen – Web Information Systems and Mining, 2012 – Springer … Meanwhile they lack the area portability. Machine learning methods need to apply a lot of deep natural language processing (NLP) technologies which inevitably produce a lot of noise. SVM methods * Corresponding author. Page 2. … Related articles All 4 versions
Using Tweets To Summarise News Stories D Tanner-Davies, J McNaught – 2014 – danieltannerdavies.co.uk Page 1. University of Manchester Computer Science Department Using Tweets To Summarise News Stories Author: Daniel Tanner-Davies Supervisor: John McNaught April 29, 2014 Page 2. Abstract A large amount of data is …
Search Result Ontologies for Digital Libraries E Reiterer – The Semantic Web: Semantics and Big Data, 2013 – Springer … library. Current limitations in terms of auto- matic extraction of ontologies should be overcome with the help of seed ontologies, deep natural language processing techniques and weights ap- plied to newly added concepts. The … Related articles All 4 versions
Towards domain independent why text segment classification based on bag of function words K Tanaka, T Takiguchi, Y Ariki – AI 2012: Advances in Artificial Intelligence, 2012 – Springer … How- ever, since it requires heavy language analysis and deep natural language processing skill, it is not easily adaptable to different languages. Tanaka [4] proposed a machine learning [1, 2] method based on BOW to perform WTS classification. … Related articles All 4 versions
Named entity recognition for ontology population using background knowledge from Wikipedia Z Zhang, F Ciravegna – … and Knowledge Discovery Using the Web: …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 5 Related articles All 2 versions
Proof-checking mathematical texts in controlled natural language M Cramer – 2013 – naproche.net … Computational linguistics can make use of statistical methods, of rule-based methods, or of a combination thereof. A separate methodologi- cal division of computational linguistic is that between deep natural language processing and shallow natural language processing. … Related articles All 5 versions
Multi-Entity Polarity Analysis in Financial Documents JZ Ferreira, J Rodrigues, M Cristo… – Proceedings of the 20th …, 2014 – dl.acm.org … We evaluated models based on the partition of documents into fragments according to the en- tities they cite. We used several heuristics to segment documents based on shallow and deep natural language processing (NLP). …
Semantic NLP-based information extraction from construction regulatory documents for automated compliance checking J Zhang, NM El-Gohary – Journal of Computing in Civil Engineering, 2013 – ascelibrary.org Page 1. Accepted Manuscript Not Copyedited 1 Graduate Student, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801. 2 Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. … Cited by 3 Related articles
Tapping Into The Power of Automatic Scoring WH Gomaa, AA Fahmy – the eleventh International Conference on …, 2011 – researchgate.net … C-rater’s technology uses “bag of words approach” in which deep natural language processing is used to assess whether a student response contains text which could be considered a paraphrase of the concepts listed in the rubric for an item. … Cited by 1 Related articles
Knowledge extraction for question titling CG Pérez, J Cardeñosa – Flexible Query Answering Systems, 2011 – Springer … paraphrasing. Their automatic processing will call at deep natural language processing techniques, accompanied by domain knowledge, computational lexicons and grammars for natural language understanding and generation. … Related articles All 6 versions
Ontology-Based Knowledge Capture & Sharing in Enterprise Organisations AS Dadzie, V Uren, F Ciravegna – … , Wong, W., Liu, W, Bennamoun, M. …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 1 Related articles All 3 versions
Towards web search by sentence queries: asking the web for query substitutions Y Yamamoto, K Tanaka – Database Systems for Advanced Applications, 2011 – Springer … expressions for written language to ones for spoken language based on oc- currence in written and spoken language corpora [5]. As in these studies, most approaches are based on off-line processing through machine learning or deep natural-language processing, and they … Cited by 1 Related articles All 5 versions
Question Answering for Alzheimer Disease Using Information Retrieval. S Bhattacharya, L Toldo – CLEF (Online Working Notes/ …, 2012 – homepage.cs.uiowa.edu … Challenge’2. ‘Watson’ used Apache UIMA’s real-time content analytics3 in conjugation with deep natural language processing, information retrieval, machine learning, etc. to provide an- swers to open domain questions in an extremely efficient way. … Cited by 2 Related articles All 2 versions
Context based Meaning Extraction for HCI using WSD algorithm: A review P Saktel, U Shrawankar – Advances in Engineering, Science …, 2012 – ieeexplore.ieee.org … [7] E. Agirre and P. Edmonds (2006),” Word sense Disambiguation: Algorithms and Applications”, Springer. [8] Johan Bos and Malvina Nissim (2009),” From shallow to deep Natural language processing: A hands-on tutorial”, Springer. … Cited by 2 Related articles All 2 versions
Integrating document clustering and multidocument summarization D Wang, S Zhu, T Li, Y Chi, Y Gong – ACM Transactions on Knowledge …, 2011 – dl.acm.org … Abstractive summarization usually involves in- formation fusion, sentence compression and reformulation [Jing and McKeown 2000; Knight and Marcu 2002]. Although an abstractive summary could be more concise, it requires deep natural language processing techniques. … Cited by 16 Related articles All 7 versions
Ontology Learning and the Humanities T Burrows – Ontology Learning and Knowledge Discovery Using …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 1 Related articles All 2 versions
Comparative document summarization via discriminative sentence selection D Wang, S Zhu, T Li, Y Gong – ACM Transactions on Knowledge …, 2012 – dl.acm.org … Although an ab- stractive summary could be more concise, it requires deep natural language processing techniques. Thus extractive summaries are more feasible and practical, and in the related work, our discussion focuses on extractive document summarization. … Cited by 21 Related articles All 10 versions
Disputed sentence suggestion towards credibility-oriented web search Y Yamamoto – Web Technologies and Applications, 2012 – Springer … 3. Suggest top-k of the disputed sentences to users 3.1 Extracting Disputed Sentences from the Web Detecting sentences that other documents dispute is quite hard because it requires deep natural language processing for large corpora. To bypass this problem, Ennals et al. … Related articles All 7 versions
Developing Position Structure-Based Framework for Chinese Entity Relation Extraction P Zhang, W Li, Y Hou, D Song – ACM Transactions on Asian Language …, 2011 – dl.acm.org … based approach. In this article, we present a novel feature-based Chinese relation extraction frame- work, in which all the features do not require the Chinese word segmentation or deep natural language processing. Particularly … Cited by 1 Related articles All 8 versions
Short Answer Grading Using String Similarity and Corpus-Based Similarity WH Gomaa, AA Fahmy – International Journal of Advanced …, 2012 – researchgate.net … accuracy for short answer responses. The reason behind high accuracy is using deep natural language processing to determine the relatedness of student response to the concepts listed in the rubric for an item. The C-rater engine … Cited by 2 Related articles All 6 versions
Automated learning of social ontologies K Kotis, A Papasalouros – … and Knowledge Discovery Using the Web: …, 2011 – igi-global.com … Chapter 2. An Overview of Shallow and Deep Natural Language Processing for Ontology Learning (pages 16-37). Amal Zouaq. This chapter gives an overview over the state-of-the-art in natural language processing for ontology learning. It presents two main NLP techniques… … Cited by 1 Related articles All 2 versions
Transforming a Flat Metadata Schema to a Semantic Web Ontology: The Polish Digital Libraries Federation and CIDOC CRM Case Study C Mazurek, K Sielski, M Stroi?ski, J Walkowska… – Intelligent Tools for …, 2012 – Springer … In some cases a more meaningful table of contents might be built based on different kinds of relations (dc:relation and its subelements, especially dcterms:hasPart). Future works allowing to achieve more meaningful mapping should include deep natural language processing. … Cited by 12 Related articles All 4 versions
An efficient approach for sentence-based opinion retrieval B Li, KF Wong, L Zhou, S Feng – International Journal of Computer …, 2011 – World Scientific … than one topic. (2) Deep natural language processing techniques eg, discourse analysis, collocation identification [26] may help to understand the meaning of opinion so as to improve the accuracy of opinion retrieval. (3) The … Cited by 1 Related articles All 3 versions
Symmetric and Asymmetric Properties in Korean Verbal Coordination: A Computational Implementation JB Kim, J Yang – Language and Information, 2011 – kyunghee.ac.kr Page 1. Symmetric and Asymmetric Properties in Korean Verbal Coordination: A Computational Implementation Jong-Bok Kim? Jaehyung Yang†‡ Kyung Hee University Kangnam University Jong-Bok Kim & Jaehyung Yang. 2011. … Cited by 3 Related articles All 4 versions
Optimizing Persian Text Summarization Based on Fuzzy Logic Approach F Kiyomarsi, FR Esfahani – 2011 International Conference on Intelligent …, 2011 – ipcsit.net … However, abstractive approaches require deep natural language processing such as semantic representation, inference and natural language generation, which have yet to reach a mature stage nowadays [7]. Automatic text summarization is the technique in which a computer … Cited by 4 Related articles All 4 versions
Exploring the Potential of Speech Recognition to Support Problem Solving and Reflection M Mavrikis, B Grawemeyer, A Hansen… – Open Learning and …, 2014 – Springer … process in an effort to respond on the system’s prompts. As the wizards were avoiding performing deep natural language processing they could not help the students. We observed similar situations in the recordings of the rest …
A Labeled Graph Kernel for Relationship Extraction G Simões, H Galhardas, D Matos – arXiv preprint arXiv:1302.4874, 2013 – arxiv.org … limited size around them. The advantage of this kernel is its simplicity since it does not need deep Natural Language Processing tools to preprocess the sentences in order to compute the kernel. However, its major advantage … Cited by 1 Related articles All 2 versions
Conversational CBR MM Richter, RO Weber – Case-Based Reasoning, 2013 – Springer … 17, Sect. 17.?3.?7) with synonyms, such as word sense disambiguation. At the extreme of complexity are deep natural language processing and the use of distributed representations (see Chap. 17, Sect. 17.?3.?5). 20.5.2 Dialogue Management. … Related articles
Tweet Sentiment Analytics with Context Sensitive Tone-Word Lexicon A Babour, JI Khan – Proceedings of the 2014 IEEE/WIC/ACM …, 2014 – dl.acm.org … Our technique builds on these latest resources. We refrain from deep natural language processing (NLP) analysis. Rather we limit ourselves to lexical semantic analysis and three structural linguistic features namely- word proximity, order of occurrence, and frequency. …
Sequential pattern based multi document summarization—An exploratory approach S Alias, SK Muhammad – Research and Innovation in …, 2013 – ieeexplore.ieee.org … of two similarity measures. Going into deep Natural Language Processing, [9] analyzed the Discourse Structure of the text in order to produce a coherence summary by using Lexical or coreference chain. Here, the main topics … Related articles
Named entity recognition and identification for finding the owner of a home page V Plachouras, M Rivière, M Vazirgiannis – Advances in Knowledge …, 2012 – Springer … Minkow et al. [11] apply a CRF model to recognize names in emails, using features which are primarily based on gazetteers for per- son first and last names, names of organizations and locations, but not using deep natural language processing. Zhu et al. … Cited by 1 Related articles All 3 versions
Explore Dissimilarity Method for Summarization C Guo – Journal of Convergence Information Technology, 2011 – aicit.org … The problem of abstractive approaches is that they require deep natural language processing such as semantic representation, inference and natural language generation, which have yet to reach a mature stage nowadays. … Related articles All 2 versions
The Era of Cognitive Systems: An Inside Look at IBM Watson and How it Works R High – Redguites for Business Leaders, 2012 – developer.ibm.com … rule. They might be precise, but not necessarily very accurate. Deep natural language processing To overcome the limitations of brick building, we shifted to using steel and reinforced concrete for larger buildings. Likewise, we … Cited by 2 Related articles All 6 versions
[BOOK] Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances W Wong, W Liu, M Bennamoun, IGI Global – 2011 – eprint13.blacknight.ie Page 1. Wilson Wong The University of Western Australia, Australia Wei Liu The University of Western Australia, Australia Mohammed Bennamoun The University of Western Australia, Australia Ontology Learning and Knowledge Discovery Using the Web: … Cited by 3 Related articles All 5 versions
Enhanced ontology-based indexing and searching S Thenmalar, TV Geetha – Aslib Journal of Information …, 2014 – emeraldinsight.com
Summarization by domain ontology navigation T Andreasen, H Bulskov – International Journal of Intelligent …, 2013 – Wiley Online Library … Words and/or phrases must be extracted from the text and mapped into the ontology. This is a knowledge extraction problem, and obviously such knowledge extraction can span from full deep natural language processing (NLP) to simplified shallow processing methods. … Related articles All 5 versions
Ranking on data manifold with sink points XQ Cheng, P Du, J Guo, X Zhu… – Knowledge and Data …, 2013 – ieeexplore.ieee.org … There are mainly two kinds of approaches for update summarization, one is abstractive summarization [25], [14], in which some deep natural language processing techniques are leveraged to compress sentences or to reorganize phrases to produce a summary of the text. … Cited by 17 Related articles All 18 versions
Multiple documents summarization based on evolutionary optimization algorithm RM Alguliev, RM Aliguliyev, NR Isazade – Expert Systems with Applications, 2013 – Elsevier … 2010). Although an abstractive summary could be more concise, it requires deep natural language processing techniques. Thus, an extractive summary is more feasible and has become the standard in document summarization. … Cited by 6 Related articles All 5 versions
An Improved Approach for Word Ambiguity Removal P Saktel, U Shrawankar – arXiv preprint arXiv:1304.7282, 2013 – arxiv.org … [7] E. Agirre and P. Edmonds (2006),” Word sense Disambiguation: Algorithms and Applications”, Springer. [8] Johan Bos and Malvina Nissim (2009),” From shallow to deep Natural language processing: A hands-on tutorial”, Springer. … Related articles All 3 versions
State of the Art NLP: Multilingualism and Semantic Parsing in Information Retrieval and Extraction T MENDT, P MURIITHI, E SAMOTA… – 2014 – info.univ-tours.fr Page 1. Université François Rabelais – Tours, antenne de Blois Laboratoire d’Informatique (UPRES EA n o 2101) State of the Art NLP: Multilingualism and Semantic Parsing in Information Retrieval and Extraction Authors Tamara …
Cloud programming paradigms for technical computing applications G Fox, D Gannon – Proc. Cloud Futures Workshop, 2012 – grids.ucs.indiana.edu … Foundation. 12. Kyoto University Daisuke Kawahara and Sadao Kurohashi of Kyoto University have been developing a search engine infrastructure, TSUBAKI, which is based on deep Natural Language Processing. While most … Cited by 12 Related articles All 5 versions
Extracting Summary from Documents using K-mean Clustering Algorithm DVS Ramana – IJCSNS, 2014 – paper.ijcsns.org … MMR approach used earlier. The advantages of the introduced method are: it does not use external resource except the original document given summary and deep natural language processing is not required. This method has …
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 robust method for text summarization, most of multi-document summarization focus on …
Algorithm to Resolve Anaphoric Ambiguity of Text Summarization A Thakur – 2013 – dspace.thapar.edu Page 1. Algorithm to Resolve Anaphoric Ambiguity of Text Summarization Thesis submitted in partial fulfillment of the requirements for the award of degree of Master of Engineering in Software Engineering Submitted By Avnish Thakur (Roll No. 801131007) … Related articles
The cloud will change everything. JR Larus – ASPLOS, 2011 – research.microsoft.com … We implemented the system and evaluated the rendering and data transferring performance.” }, { Title”: “Deep Natural Language Processing for Improving a Search Engine Infrastructure using Windows Azure”, “Type”: “Talk”, “Key … Cited by 6 Related articles All 11 versions
An optimization approach to automatic generic document summarization RM Alguliev, RM Aliguliyev… – Computational …, 2013 – Wiley Online Library … Text summarization is a complex task, which ideally would involve deep natural language processing capacities. To simplify the issue, current research is focused on extractive-summary generation. Sentence based extractive … Cited by 2 Related articles All 3 versions
DESAMC+ DocSum: Differential evolution with self-adaptive mutation and crossover parameters for multi-document summarization RM Alguliev, RM Aliguliyev, NR Isazade – Knowledge-Based Systems, 2012 – Elsevier … Abstraction can be described as reading and understanding the text to recognize its content that is then compiled in a concise text [37]. Although an abstractive summary could be more concise, it requires deep natural language processing (NLP) techniques. … Cited by 13 Related articles All 3 versions
Extraction of ontology schema components from financial news M Vela – 2012 – scidok.sulb.uni-saarland.de Page 1. Extraction of Ontology Schema Components from Financial News Dissertation zur Erlangung des akademischen Grades eines Doktors der Philosophie der Philosophischen Fakultät der Universität des Saarlandes vorgelegt von Mihaela Vela aus Timisoara (Rumänien) … Related articles All 3 versions
Text mining improves prediction of protein functional sites KM Verspoor, JD Cohn, KE Ravikumar, ME Wall – PloS one, 2012 – dx.plos.org PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world. Cited by 13 Related articles All 13 versions
Contextual sentence decomposition with applications to semantic full-text search E Haussmann – 2011 – ad.informatik.uni-freiburg.de … This rules out approaches performing deep natural language processing, for example the construction complete syntactic parse trees. The approaches we provide work on a more shallow and efficient level of natural language processing. … Cited by 3 Related articles All 4 versions
Using Clouds for Technical Computing BDC Catlett – Cloud Computing and Big Data, 2013 – books.google.com … service. 7.12. Kyoto University Daisuke Kawahara and Sadao Kurohashi of Kyoto University have been developing a search engine infrastructure, TSUBAKI [71], which is based on deep Natural Language Processing. While … Related articles
A music information system automatically generated via web content mining techniques M Schedl, G Widmer, P Knees, T Pohle – Information Processing & …, 2011 – Elsevier This article deals with the problem of mining music-related information from the Web and representing this information via a music information system. Novel tec. Cited by 13 Related articles All 7 versions
Frequently asked questions web pages automatic text summarization YM Shaalan – 2011 – dar.aucegypt.edu Page 1. The American University in Cairo School of Sciences and Engineering FREQUENTLY ASKED QUESTIONS WEB PAGES AUTOMATIC TEXT SUMMARIZATION A Thesis submitted to Department of Computer Science and Engineering … Related articles All 3 versions
Utilizing graph-based representation of text in a hybrid approach to multiple documents summarization MA Sayed – 2014 – dar.aucegypt.edu Page 1. All Rights Reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. SCHOOL OF SCIENCES AND ENGINEERING Utilizing Graph-based Representation of Text in a Hybrid … Related articles
Domain-sensitive topic management in a modular conversational agent framework D Macias Galindo – 2014 – researchbank.rmit.edu.au … Modularity can range from additional knowledge domains to new capabilities or behaviours of the Toy, such as story-telling or becoming a math tutor. Regarding its conversational capabilities, the Toy does not perform deep natural language processing over user inputs. …
Automatic Methods To Disambiguate Geospatial Queries C Hafernik – 2011 – ida.mtholyoke.edu Page 1. I give permission for public access to my thesis and for any copying done at the discretion of the archives librarian and/or the College librarian …………… June 25, 2007 Carolyn T. Hafernik Page 2. Automatic Methods To Disambiguate Geospatial Queries … Related articles All 5 versions