Automated Reasoning & Question Answering

Notes:

A question answering (QA) system is a computer program that is designed to answer questions posed by human users. There are several different approaches to implementing QA systems, but one common approach is to use a structured database of knowledge, known as a knowledge base, to generate answers.

In this approach, the QA system uses natural language processing techniques to understand the question, and then searches the knowledge base for relevant information. The system may also use machine learning algorithms and other techniques to process and interpret the data in the knowledge base, and to generate a coherent and accurate answer.

QA systems can be used in a variety of contexts, such as customer service, education, or research, and can be implemented in a variety of platforms, such as messaging apps, voice assistants, or web-based interfaces.

Automated reasoning is the process of using algorithms and software tools to reason and make decisions based on logical principles and available data. There are various tools and techniques that can be used to support automated reasoning, including:

Classical logics and calculi: These are formal systems of logic that are used to represent and reason about the relationships between statements and their logical consequences. Examples include propositional logic, first-order logic, and modal logic.
Fuzzy logic: This is a type of logic that allows for the representation and manipulation of uncertainty and imprecision. It is often used in artificial intelligence systems to deal with situations where the data is noisy or incomplete.
Bayesian inference: This is a method of statistical inference that is based on Bayes’ theorem, which allows for the calculation of the probability of an event based on prior knowledge and observed data. It is often used in artificial intelligence systems to make predictions or decisions based on uncertain data.
Reasoning with maximal entropy: This is a method of statistical inference that is based on the principle of maximum entropy, which states that, given a set of constraints, the probability distribution that is most likely to be true is the one that maximizes the entropy of the system. It is often used in artificial intelligence systems to make predictions or decisions based on uncertain data.

Automated reasoning can be used with emotion corpora, which are collections of data or text that are annotated with information about emotions, to support the development and evaluation of artificial intelligence systems that are capable of detecting and recognizing emotions.

For example, an automated reasoning system could be trained on an emotion corpus to classify text as expressing a particular emotion, such as happiness, sadness, anger, or fear. The system could then be used to classify new text as expressing one of these emotions, or to identify patterns in the data that are indicative of particular emotions.

In addition, an automated reasoning system could be used to analyze an emotion corpus to identify the most important features or characteristics that are associated with different emotions, and to develop algorithms or models that can accurately predict the emotions that are likely to be expressed in new text.

Resources:

aarinc.org .. association for automated reasoning
cadeinc.org .. conference on automated deduction

Wikipedia:

References:

Decision support for selection of cloud service providers
T Sander, S Pearson – GSTF Journal on Computing (JoC), 2018 – dl6.globalstf.org
… However this information cannot yet be used for the automated reasoning in the tool and should thus only be used where necessary … ie Boolean expression built up using & and v as logical operators) in intermediate variables (IMs) and/or (question, answer) pairs and as actions …

What action causes this? towards naive physical action-effect prediction
Q Gao, S Yang, J Chai, L Vanderwende – … of the 56th Annual Meeting of …, 2018 – aclweb.org
… Despite tremendous progress in knowledge rep- resentation, automated reasoning, and machine learning, artificial agents still lack the understand- ing of … have seen an increasing amount of work integrating language and vision, for example, visual question answer- ing (Antol …

Enumerating justifications using resolution
Y Kazakov, P Sko?ovský – … Joint Conference on Automated Reasoning, 2018 – Springer
… Automated Reasoning. Download book …

An interoperable model for the intelligent content object based on a knowledge ontology and the scorm specification
XH Zhu, TJ Wu, HC Chen – Journal of Educational …, 2018 – journals.sagepub.com
Based on the sharable content object concept of advanced distributed learning, an ontology-based intelligent content object (ICO) that can automatically reason …

Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
R Das, T Munkhdalai, X Yuan, A Trischler… – arXiv preprint arXiv …, 2018 – arxiv.org
… They enable automated reasoning, eg, the ability to infer unobserved facts from observed evidence and to make logical “hops,” and … state changes in procedural text and (ii) conditions on its own constructed knowledge graphs to improve downstream question answering on the …

Automated Reasoning in the Age of the Internet
A Bundy, K Nuamah, C Lucas – International Conference on Artificial …, 2018 – Springer
… In order for automated reasoning to combine information in diverse formats, these must all be curated into a common format … 31(3), 59–79 (2010)CrossRefGoogle Scholar. 4. Green, CC, Raphael, B.: The use of theorem-proving techniques in question-answering systems …

Reasoning and Consciousness Teaching a Theorem Prover to let its Mind Wander
U Furbach, C Schon – AITP 2018, 2018 – aitp-conference.org
… In MP Bonacina, editor, CADE-24, LNCS, 2013. [3] U. Furbach, I. Glöckner, and B. Pelzer. An application of automated reasoning in natural language question answering. AI Commun., 23 (2-3): 241–265, 2010. [4] U. Furbach and C. Schon …

A Methodology for a Criminal Law and Procedure Ontology for Legal Question Answering
B Fawei, JZ Pan, M Kollingbaum, AZ Wyner – Joint International Semantic …, 2018 – Springer
… To develop question answering systems, ontologies can be used to develop domain-specific semantic information … take a legal ontology along with rules to be core elements in this process as the link all the necessary legal elements of a case and support automated reasoning …

Patient Selection for Clinical Trials Using Temporalized Ontology-Mediated Query Answering
F Baader, S Borgwardt, W Forkel – … of the The Web Conference 2018 on …, 2018 – dl.acm.org
… Track: First International Workshop on Hybrid Question Answering with Structured and Unstructured Knowledge (HQA’18) … In the future, we aim to develop effective procedures that enable automated reasoning over knowledge expressed in this way …

Variational Knowledge Graph Reasoning
W Chen, W Xiong, X Yan, W Wang – arXiv preprint arXiv:1803.06581, 2018 – arxiv.org
… 1 Introduction Automated reasoning, the ability for computing systems to make new inferences from the observed evidence, has attracted lots of attention from the research community … Systems for this task are essential to complex question answering applica- tions …

When, Where, Who, What or Why? A Hybrid Model to Question Answering Systems
EG Cortes, V Woloszyn, DAC Barone – International Conference on …, 2018 – Springer
… Question answering (QA) is a specific Computer Science task within the fields of Information Retrieval and Natural … of Computer Science that vary from advanced natural language processing, information retrieval, knowledge representation, automated reasoning, to machine …

Engineering Of Intelligent Personal Assistant For Product Range: A Review Of The Literature
VS Vetrov – «RUSSIAN ECONOMY: GOALS, CHALLENGES AND …, 2018 – fa.ru
… An application of automated reasoning in natural language question answering//AI Communications Volume 3, 2010 (241-265) 3. Izhak-Ratzin R., Hyunggon, van der Schaar PM Reinforcement Learning in BitTorrent Systems//INFOCOM, 2011 Proceedings IEEE (Conference …

Query Answering by Deductive and Analogical Reasoning in a Semantic Vector Space
D Li, P Sutor, A Raglin – cogsys.org
… In automated reasoning, however, analogy is usually treated as completely separate from deduction … Lee, M., He, X., Yih, W.-t., Gao, J., Deng, L., & Smolensky, P. (2015). Reasoning in vector space: An exploratory study of question answering. arXiv preprint arXiv:1511.06426 …

An Undergraduate Curriculum Model for Intelligence Science and Technology
J Cheng, R Huang, Q Jin, J Ma… – 2018 IEEE SmartWorld …, 2018 – ieeexplore.ieee.org
… 236 Page 4. Course Name Brief Course Description data analysis Automated Reasoning and Proving … Natural Language Processing Cover the most basic contents of natural language understanding, translation, summarization, generation, question- answering, dialogue, etc …

Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences
D Khashabi, S Chaturvedi, M Roth… – Proceedings of the …, 2018 – aclweb.org
… In particular, in natural language processing (NLP) it has been studied under various settings, such as multiple- choice Question-Answering (QA) (Green Jr … 2 Relevant Work Automated reasoning is arguably one of the ma- jor problems in contemporary AI research …

IBM Watson Chatbots
M Biswas – Beginning AI Bot Frameworks, 2018 – Springer
… Its core implementations use natural language processing, information retrieval, knowledge representation, automated reasoning, and machine-learning technologies in the field of open domain question answering. It is used for quick AI-based solutions …

A review of spatial expert systems: Do they still have a role to play?
D Demetriou – … on Remote Sensing and Geoinformation of the …, 2018 – spiedigitallibrary.org
… After a growth period of spatial ES in the 1990s followed by slower growth in the 2000s, the decline that has occurred during the last seven years is dramatic, raising a twofold question: do they still have a role to play and what is the future of spatial automated reasoning …

An Answer Set Programming Based Approach To Representing And Querying Textual Knowledge
DR Pendharkar, G Gupta, V Gogate, V Ng – 2018 – utdallas.edu
… Using the generated knowledge bases, the computer is then able to solve complex tasks like question answering, summarization, automated reasoning, medical diagnosis and many more. Many of these complex tasks, mentioned above …

Hierarchical Reinforcement Learning with Abductive Planning
K Yamamoto, T Onishi, Y Tsuruoka – arXiv preprint arXiv:1806.10792, 2018 – arxiv.org
… Question answering as abduc- tion : A feasibility study at NTCIR QAC1 … In Proceedings of the 1st Workshop on Natural Language Processing and Automated Reasoning (NLPAR), number 1044 in CEUR Workshop Proceedings, pages 76–87, A Corunna, Spain, 2013 …

Students Conversation Management System
AR Iyanda, OD Ninan, DJ Odejimi – 2018 – mecs-press.org
… [6] TL Acorn and SH Walden. “SMART: Support management automated reasoning technology for Compaq customer service” … 2007, January. [13] Waheeb Ahmed, Ajusha Dasan, Babu Anto P. “Developing an Intelligent Question Answering System”, International Journal of …

Chatbots for Education-Trends, Benefits and Challenges
AA Georgescu – The International Scientific Conference eLearning and …, 2018 – ceeol.com
… was created as a question answering computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering [13 …

Artificial Intelligence for Conversational Robo-Advisor
MY Day, JT Lin, YC Chen – 2018 IEEE/ACM International …, 2018 – ieeexplore.ieee.org
… Retrieval-based model: A retrieval-based model is similar to a question-answering system, which … Turing in 1950 highlights four dimensions that must be satisfied by computer systems: natural language processing (NLP), knowledge representation, automated reasoning, and ML …

RCE-OIE: Open Information Extraction Using a Rule-Based Clause Extraction Engine for Semantic Applications
D Thenmozhi, C Aravindan – Recent Findings in Intelligent Computing …, 2018 – Springer
… 1545 (2011)Google Scholar. 8. Furbach, U., Glockner, I., Helbig, H., Pelzer, B.: LogAnswer—a deduction-based question answering system (system description). In: International Joint Conference on Automated Reasoning, pp. 139–146. Springer (2008)Google Scholar. 9. Hovy …

Reasoning About Time Martin Charles Golumbic
MC Golumbic – cs.haifa.ac.il
Page 1. Reasoning About Time Martin Charles Golumbic Bar-Ilan University, Ramat-Gan, Israel golumbic@cs.biu.ac.il 1. Introduction Reasoning about time is essential for applications in arti cial intelligence and in many other disciplines …

Insights for Configuration in Natural Language
AFB Santa, E Vareilles… – CEUR …, 2018 – hal-mines-albi.archives-ouvertes.fr
… are improved with natural language generation (NLG) in order to produce responses, the system then becomes a question answering system (QAS) [13] … It encodes a query by applying automated reasoning, machine learning and several other techniques to analyze the speech …

Automatic Understanding And Formalization Of Natural Language Geometry Problems Using Syntax-Semantics Models
W Gan, X Yu – INTERNATIONAL JOURNAL OF …, 2018 – pdfs.semanticscholar.org
Page 1. International Journal of Innovative Computing, Information and Control ICIC International c?2018 ISSN 1349-4198 Volume 14, Number 1, February 2018 pp. 83–98 AUTOMATIC UNDERSTANDING AND FORMALIZATION …

Formal ontology for discourse analysis<? br?> of a corpus of court interpreting
A Pease, JC Pease, AKF Cheung – Babel, 2018 – jbe-platform.com
… Hoboken (NJ): Wiley-Blackwell. Jacobsen, B. 2004. “Pragmatic meaning in court interpreting: An empirical study of additions in consecutively interpreted question-answer dialogues”. Hermes 32: 237–249. James F. Allen, C. R. P. 1980. “Analyzing intention in utterances” …

Insights for Configuration in Natural Language
AF Barco, E Vareilles, CI Osorio – 20 th International Configuration …, 2018 – eventhelpr.com
… are improved with natural language generation (NLG) in order to produce responses, the system then becomes a question answering system (QAS)[13] … It encodes a query by applying automated reasoning, machine learning and several other techniques to analyze the speech …

A Novel Hybrid Knowledge Retrieval Approach for Online Customer Service Platforms
P Beduè, R Graef, M Klier, JF Zolitschka – 2018 – aisel.aisnet.org
… related to a small amount of search words (cf., eg research area of information retrieval (Campos et al., 2015; Carpineto and Romano, 2012)) or to answer questions by combining knowledge in a constructed answer (cf., eg research area of question answering (Höffner et al …

Introduction to Artificial Intelligence and Cognition
M Skilton, F Hovsepian – The 4th Industrial Revolution, 2018 – Springer
… can be traced back to Gottfried Leibniz, who envisaged a machine that could help resolve complex legal cases using an automated reasoning machine … Four of the question/answer pairs are produced here in their original form, in the interest of accuracy of the information being …

The Knowledge Object Reference Ontology (KORO): A formalism to support management and sharing of computable biomedical knowledge for learning health …
AJ Flynn, CP Friedman, P Boisvert… – Learning Health …, 2018 – Wiley Online Library
Skip to Main Content …

Learning Search Policies in Large Commonsense Knowledge Bases by Randomized Exploration
A Sharma, KM Goolsbey – 2018 – cogsys.org
… As discussed above, when the size of the training set is zero, the question answering (Q/A) performance corresponds to the baseline for the experiment … Premise selection for mathematics by corpus analysis and kernel methods. Journal of Automated Reasoning, 52, 191–213 …

ENTER2018@Jönköping – digital tourism: engagement, content and networks: 23–26 January 2018, Jönköping, Sweden
ICC Chan, R Law – Anatolia, 2018 – Taylor & Francis
… He introduced the digital assistant, IBM Watson, which was a question answering computing system created by applying natural language interactions, information retrieval, knowledge representation, automated reasoning and machine learning technologies …

Automating “human-like” example-use in mathematics
A Pease, U Martin – ceur-ws.org
… Also of interest are discussion fora which allow rapid informal interaction and problem solving; in seven years the community question answering system for re- search mathematicians MathOverflow has around 70,000 users and has … 2.3 Examples in Automated Reasoning …

Ontology in Software Engineering
SF Pileggi, AA Lopez-Lorca, G Beydoun – acis2018.org
… We will attempt to harness their potential, including automatic reasoning, as a tool to enable the verification and validation of these systems … “Exploring multiple ontologies and WordNet framework to expand query for question answering system” …

LOD-CS2013: Multileaming through a semantic representation of IEEE computer science curricula
N Piedra, ET Caro – Global Engineering Education Conference …, 2018 – ieeexplore.ieee.org
… An automatic reasoning tool is used to extract from the ontology the concepts and the logical relationships between concepts to determine whether logical … In this way, Natural Language Processing (NLP) can be used to achieve advanced online question answering services …

An Approach for Automatic Categorization of Arabic Normative Provisions
I Berrazega, R Faiz – International Journal on Artificial Intelligence Tools – World Scientific
… Indeed, setting up efficient automated reasoning processes requires a good preparation of suitable techniques and tools adapted to … NLP-based approaches for semantic annotation have been exploited in various applications namely question answering, information retrieval …

Building an all-source analytics capability for coalition interoperability
EK Bowman – … , Integration, and Networking for Persistent ISR …, 2018 – spiedigitallibrary.org
… information from across the Intelligence Community more accessible, available for fusion and amenable to automated reasoning, and 4 … Adaptive human-agent team development within dynamic military contexts • Using knowledge graphs to improve question-answering and for …

Visualization and Forecast Analysis of Science and Technology Intelligence Based on Knowledge Graph
J Rui, S Yu, H Yan, S Ding, B Wang… – … and Applications for …, 2018 – ieeexplore.ieee.org
… Using Semantic Networks, sentences in natural language can easily express and store in graphs for machine translation [5], question answering systems [6] and natural language understanding [7]. With the … At the same time, automatic reasoning also becomes more efficient …

Symbolic Artificial Intelligence
ND Rodríguez – 2018 – perso.telecom-paristech.fr
… Because is a decidable7 fragment of FOL, therefore, amenable for automated reasoning • Because generating justifications for entailment8 is possible9 • Ex … Applications: Information retrieval, search, question answering, m-Government emergency response services [1] or …

Knowledge-Based Approach to Planning: A Case Study-Based Approach
S Sen, J Shah, M Sohoni – Geospatial Infrastructure, Applications and …, 2018 – Springer
… Info sharing and automated question answering for farmers. Coastal area planning … While such knowledge would be machine readable and amenable to automated reasoning, they would also be translatable to readable text and vice versa [42] …

A Survey on Semantic Parsing
A Kamath, R Das – arXiv preprint arXiv:1812.00978, 2018 – arxiv.org
… The meaning representation generated goes beyond shallow identification of roles and objects in a sentence to the point where it enables automated reasoning … Berant et al. [2013] learn a semantic parser from question answer pairs on Freebase …

Overview Of Artificial Intelligence
N Pundit, A Rewari – bitsindriinternational.org
… general knowledge quiz). Watson applied advanced NLP, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to this field of open domain question answering. In 2011, IBM …

Towards security defect prediction with AI
CD Sestili, WS Snavely, NM VanHoudnos – arXiv preprint arXiv …, 2018 – arxiv.org
… Index Terms—deep learning, static analysis, memory networks, question-answering … It establishes a target for question-answering AI systems, such that any such system must be able to achieve high performance on the bAbI dataset to be considered successful …

Discourse in Multimedia: A Case Study in Information Extraction
M Sachan, KA Dubey, EH Hovy, TM Mitchell… – arXiv preprint arXiv …, 2018 – arxiv.org
… Discourse analysis has been shown to be useful for many NLP tasks such as question answering (Chai and Jin 2004b; Lioma, Larsen, and Lu 2012b; Jansen, Surdeanu, and Clark 2014), summarization (Louis, Joshi, and Nenkova 2010b) and information extraction (Kitani …

Applying the Closed World Assumption to SUMO-based Ontologies
J Álvez, I Gonzalez-Dios, G Rigau – arXiv preprint arXiv:1808.04620, 2018 – arxiv.org
Page 1. arXiv:1808.04620v1 [cs.AI] 14 Aug 2018 Applying the Closed World Assumption to SUMO-based Ontologies Javier ´Alvez1, Itziar Gonzalez-Dios2, and German Rigau3 1 LoRea Group, University of the Basque Country …

Reasoning over RDF Knowledge Bases using Deep Learning
M Ebrahimi, MK Sarker, F Bianchi, N Xie… – arXiv preprint arXiv …, 2018 – arxiv.org
… Automated reasoning, attempting to conduct logical reasoning algorithmically, has been a long-standing focus of general artificial intelligence with wide application in knowledge base completion, natural language understanding, question answering, agent planning and etc …

A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications
T Wu, G Qi, C Li, M Wang – Sustainability, 2018 – mdpi.com
… representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building …

Non-Clausal Multi-ary ?-Generalized Resolution Calculus for a Finite Lattice-Valued Logic
Y Xu, J Liu, X He, X Zhong, S Chen – International Journal of …, 2018 – atlantis-press.com
… checking and testing [10], data structure verification [11], security protocols automated verification [12], question answering systems [13, 14], inconsistency … Up to now, many researchers have made investigation on resolution-based automated reasoning in the framework of fuzzy …

CoUSBi: A Structured and Visualized Legal Corpus of US State Bills
AL Kalouli, L Vrana, VM Fabella, L Bellani… – LREC 2018, 2018 – lrec-conf.org
… design automatic systems that can shed light on aspects of legislative reality, eg answer specific queries in question-answering systems or in … Another strand of research is con- cerned with automatic reasoning on legal text, bridging the gap between law and artificial intelligence …

Novel Methods for Reasoning with Uncertain Hard and Soft Data using Probabilistic and Belief Theoretic Methods
RC Nunez Sanchez – 2018 – scholarlyrepository.miami.edu
… ones presented in this manuscript. • Question Answering Systems. Question answering systems aim at auto … Unlike existing information retrieval systems (eg, search engines), which sim- ply render a list of matching documents, the main objective of question answer …

Generating Post-Hoc Rationales of Deep Visual Classification Decisions
Z Akata, LA Hendricks, S Alaniz, T Darrell – Explainable and Interpretable …, 2018 – Springer
… Automatic reasoning and explanation has a long and rich history within the artificial intelligence community (Biran and McKeown 2014 … specifically how to backpropagate through a sampling mechanism, have recently been applied to visual question answering (Andreas et al …

Logic programming applications: What are the abstractions and implementations?
YA Liu – arXiv preprint arXiv:1802.07284, 2018 – arxiv.org
… Indeed, the original application of Prolog, the first and main logic programming language, was natural language pro- cessing (NLP) [PS02], and a more recent application in NLP helped the IBM Watson question answering system win the Jeopardy Man vs …

Deep Learning—A New Era in Bridging the Semantic Gap
U Markowska-Kaczmar, H Kwa?nicka – … the Semantic Gap in Image and …, 2018 – Springer
The chapter deals with the semantic gap, the well-known phenomenon in the area of vision systems. Despite the significant efforts of researchers, the problem of how to overcome the semantic gap…

Sensemaking Research Roadmap
KP Subbalakshmi, A Galstyan, R Chellappa, C Clancy – 2018 – apps.dtic.mil
… Another relevant example is DARPA’s Communicating with Computers program (CWiC), where one of the use-cases focused on building automated reasoning agents that can help biologists to make sense of vast biomedical literature …

A Chinese legal intelligent auxiliary discretionary adviser based on GA-BP NNs
N Zhang, Y Pu, S Yang, J Gao, Z Wang… – The Electronic …, 2018 – emeraldinsight.com
… or as an integrated component within a CBR system. Deep neural networks (DNNs) have also been used to build a legal question-answering system (Kim et al., 2015). The idea behind legal expert systems is attractive because …

A Survey of the First 20 Years of Research on Semantic Web and Linked Data
F Gandon – Revue des Sciences et Technologies de l’Information …, 2018 – hal.inria.fr
Page 1. HAL Id: hal-01935898 https://hal.inria.fr/hal-01935898 Submitted on 27 Nov 2018 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not …

Dialogue Systems and Conversational Agents for Patients with Dementia: The Human–Robot Interaction
A Russo, G D’Onofrio, A Gangemi, F Giuliani… – Rejuvenation …, 2018 – liebertpub.com
… These approaches rely on machine learning techniques and are grounded in formal languages (which enable automated reasoning) and computational linguistics theories … The user can only perform question answering in response to system-initiated speech acts. In a dialogue …

Scalable Neural Theorem Proving on Knowledge Bases and Natural Language
P Minervini, M Bosnjak, T Rocktäschel, E Grefenstette… – 2018 – openreview.net
… KBs) is a major challenge for Artificial Intelligence, with applications in machine reading, dialogue, and question answer- ing … Automated reasoning applied on text requires Natural Language Processing (NLP) tools capable of extracting meaningful knowledge from free-form text …

Toward better reasoning from natural language
A Purtee – 2018 – urresearch.rochester.edu
… These extensions sup- port applications such as problem solving, question answering, planning, and our par … Non-trivial subsets of human knowledge can be expressed in symbolic logic. Automated reasoning in formal logic is a well-studied problem with industrial strength …

Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference
M Yoshikawa, K Mineshima, H Noji, D Bekki – arXiv preprint arXiv …, 2018 – arxiv.org
… 1 Introduction RTE is a challenging NLP task where the objective is to judge whether a hypothesis H logically follows from premise(s) P. Advances in RTE have positive implications in other areas such as information retrieval, question answer- ing and reading comprehension …

Neural Logic Machines
H Dong, J Mao, T Lin, C Wang, L Li, D Zhou – 2018 – openreview.net
… Unlike NLMs, ILP relies on an external automated reasoning component. The rest of the paper is organized as follows … Our results are summarized in Table 1. For MemNN, we treat the problem of relation prediction as a question answering task …

Assessing the practice of biomedical ontology evaluation: Gaps and opportunities
MF Amith, Z He, J Bian, JA Lossio-Ventura… – Journal of biomedical …, 2018 – Elsevier
With the proliferation of heterogeneous health care data in the last three decades, biomedical ontologies and controlled biomedical terminologies play a more an.

A comparative quantitative study of utilizing artificial intelligence on electronic health records in the USA and China during 2008–2017
X Chen, Z Liu, L Wei, J Yan… – BMC medical …, 2018 – bmcmedinformdecismak …
… OR “question answering” OR “word sense disambiguation” OR “named entity recognition” OR “language modeling” OR “intelligent computing” OR “intelligent computation” OR “speech recognition” OR “smart learning” OR “knowledge graph” OR “automated reasoning” OR …

Directed Digital Hate
B Pelzer, L Kaati, N Akrami – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… 2017. [7] U. Furbach, I. Glöckner, and B. Pelzer. An application of automated reasoning in natural language question answering. AI Commun., 23(2- 3):241–265, 2010. [8] H. Hosseini, S. Kannan, B. Zhang, and R. Poovendran …

Structuring visual exploratory analysis of skill demand
AS Dadzie, EM Sibarani, I Novalija, S Scerri – Journal of Web Semantics, 2018 – Elsevier
… Open Access funded by European Research Council. Under a Creative Commons license. open access. Abstract. The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations …

Effective Broad-Coverage Deep Parsing
JF Allen, O Bahkshandeh, W de Beaumont, L Galescu… – 2018 – trips.ihmc.us
… Page 2. has a semantics clear and comprehensive enough to sup- port automated reasoning (such as deduction and intention recognition, among others) … Berant, J.; Chou, A.; Frostig, R.; and Liang P. 2013. Semantic parsing on Freebase from question-answer pairs …

Rasiowa–Sikorski Deduction Systems with the Rule of Cut: A Case Study
D Leszczy?ska-Jasion, M Ignaszak, S Chlebowski – Studia Logica – Springer
Page 1. Dorota Leszczynska-Jasion Mateusz Ignaszak Szymon Chlebowski Rasiowa–Sikorski Deduction Systems with the Rule of Cut: A Case Study Abstract. This paper presents Rasiowa–Sikorski deduction systems (R–S systems) for logics CPL, CLuN, CLuNs and mbC …

Knowledge Science, Engineering and Management: 11th International Conference, KSEM 2018, Changchun, China, August 17–19, 2018, Proceedings
W Liu, F Giunchiglia, B Yang – 2018 – books.google.com
… 3 Liangguo Wang, Jing Jiang, and Lejian Liao A Biomedical Question Answering System Based on SNOMED-CT … 117 Lei Gai, Xiaoming Wang, and Tengjiao Wang Automated Reasoning over Provenance-Aware Communication Network Knowledge in Support of Cyber …

Artificial Intelligence and its Role in Near Future
J Shabbir, T Anwer – arXiv preprint arXiv:1804.01396, 2018 – arxiv.org
… knowledge field. Such formal knowledge representation is based on knowledge using content-based indexing and searching, interpretation of scenarios, support for clinical decisions, automatic reasoning [38]. Perception; the …

Deep Learning for Math Knowledge Processing
A Youssef, BR Miller – International Conference on Intelligent Computer …, 2018 – Springer
… forms such as Content MathML, computer algebra systems [11], automated reasoning systems and proof assistants. Such ambitious applications become possible when the correct semantics of symbols and expressions can be inferred. Math Question/Answer capabilities at …

Graph-Based Collaborative Filtering with MLP
S Lu, H Chen, XZ Zhou, B Wang, H Wang… – … Problems in Engineering, 2018 – hindawi.com
Mathematical Problems in Engineering is a peer-reviewed, Open Access journal that publishes results of rigorous engineering research carried out using mathematical tools. Contributions containing formulations or results related to applications are also encouraged. The primary …

SolverBlox: algebraic modeling in datalog
C Borraz-Sánchez, D Klabjan, E Pasalic… – Declarative Logic …, 2018 – dl.acm.org
Page 1. 6SolverBlox: Algebraic Modeling in Datalog Conrado Borraz-Sánchez, Diego Klabjan, Emir Pasalic, Molham Aref Datalog is a deductive query language for relational databases. We introduce LogiQL, a language based …

Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule?based approach
M Bhushan, S Goel, A Kumar – Expert Systems, 2018 – Wiley Online Library
Page 1. ARTICLE Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule? based approach Megha Bhushan1 | Shivani Goel2 | Ajay Kumar1 1 CSED, Thapar University …

Compositional engineering frameworks for development of smart cyber-physical systems: A critical survey of the current state of progression
I Horváth, S Tepjit, Z Rusák – ASME 2018 …, 2018 – … .asmedigitalcollection.asme.org
… proposed a knowledge framework that can be used to express both declarative knowledge about the components of systems, their relations and their current state, and procedural knowledge about possible system behavior for the purpose of automated reasoning [30] …

An Introduction to Ontology Engineering
CM Keet – 2018 – open.uct.ac.za
… In addition, we take a look at the principal automated reasoning services for (OWL) ontologies, such as satisfiability checking and classification and … For instance, a question-answering system that lets the scientist chat with a library chatterbot to more easily find relevant literature …

The RLLChatbot: a solution to the ConvAI challenge
N Gontier, K Sinha, P Henderson, I Serban… – arXiv preprint arXiv …, 2018 – arxiv.org
… However, most systems are still strongly hand-crafted, and not a lot of automatic reasoning machine has been proposed … NQG is trained on the Stanford Question Answering Dataset (SQuAD) (Rajpurkar et al., 2016) to solve the inverse of the reading comprehension task …

Formal Ontology Learning from English IS-A Sentences
S Dasgupta, A Padia, G Maheshwari, P Trivedi… – arXiv preprint arXiv …, 2018 – arxiv.org
… 1. Introduction Comprehensive and consistent domain-specific ontologies are useful in building applications that can perform complex tasks such as question answering [1], machine translation [2], bio-medical knowledge mining [3], and other Semantic Web applications …

Drug knowledge bases and their applications in biomedical informatics research
Y Zhu, O Elemento, J Pathak… – Briefings in bioinformatics, 2018 – academic.oup.com
… Information extraction and document summar- ization are the two major tasks here with a few advanced tasks such as question answering [97]. The information extraction step mainly involves two tasks: named entity recognition (NER) and relation extraction …

I hate numerical analysis
G Ausiello – The Making of a New Science, 2018 – Springer
… Her research interests have been mainly devoted to knowledge representation and automatic reasoning … sites: LISP in- terpreters, algebraic manipulation systems such as Macsyma and REDUCE, reasoning systems such as PLANNER, question answering systems, auto- matic …

ComR: a combined OWL reasoner for ontology classification
C Wang, Z Feng, X Zhang, X Wang, G Rao, D Fu – Frontiers of Computer Science – Springer
… new reasoner [38]. Be- sides, the Stanford Natural Language Processing Group has proposed an approach for incorporating both of these sig- nals in a unified framework for question answering analo- gously [39]. The common …

Self-training on refined clause patterns for relation extraction
DT Vo, E Bagheri – Information Processing & Management, 2018 – Elsevier
… Representing a particular set of relationships between two or more entities in text can be used for querying and automated reasoning … (2015) have defined a set of relationships on named entities such as Person, Location, and Data to support question answering in the Korean …

Linkable Technical Documentation
S Furth – 2018 – opus.bibliothek.uni-wuerzburg.de
… These works are the basis for a large spectrum of semantic technologies that are ranging from knowledge representations over query languages to automatic reasoning. Together they enable Linked Data solutions that find more and more application areas …

An improved formula for Jacobi rotations
CF Borges, Z Majdisova, V Skala, A Monszpart… – arXiv preprint arXiv …, 2018 – arxiv.org
… Inf. Theory, vol. 64, no. 7, pp. 5156-5169, Jul. 2018. Subjects: Information Theory (cs.IT); Discrete Mathematics (cs.DM). arXiv:1702.02171 (replaced) [pdf, other] Title: Question Answering through Transfer Learning from Large Fine-grained Supervision Data …

Verifying Security Protocols using Dynamic Strategies
Y Xiong, C Su, W Huang – arXiv preprint arXiv:1807.00669, 2018 – arxiv.org
… Page 3. At the same time, fast progress has been unfolding in machine learning applied to tasks that involve logical inference, such as nat- ural language question answering [47], knowledge base completion [46] and premise selection in the context of theorem proving [28] …

Words Count: The Empirical Relationship between Brief Writing and Summary Judgment Success
SB Spencer, A Feldman – Legal Writing: J. Legal Writing Inst., 2018 – HeinOnline
… The “associative system” compares new stimuli to what we know about the world, and often manifests in “quick, automatic reasoning decisions based on inferences.”20 The “rule-based” or analytic system allows for conscious consideration of stimuli in decision-making situations …

Knowledge Components and Methods for Policy Propagation in Data Flows
E Daga – 2018 – oro.open.ac.uk
… RDF Schema (RDFS) specification. The Web Ontology Language (OWL) was built with the purpose of enabling automatic reasoning over Web data, in the tradition of description logics [Antoniou and Van Harmelen (2004); W3C OWL Working Group (2012)] …

CS11001/CS11002 PROGRAMMING AND DATA STRUCTURES (3-1-0: 4 Credit)
T McGraw-Hill, O Series – cse.iitkgp.ac.in
… CS40105 SYMBOLIC LOGIC AND AUTOMATED REASONING (3-0-0 : 3 Credit) Introduction and motivation: Role of logic in Computer Science, problem representation. Basic notions: language, models, interpretations, validity, proof, decision problems in logic. decidability …

Bridging learning analytics and Cognitive Computing for Big Data classification in micro-learning video collections
D Dessì, G Fenu, M Marras, DR Recupero – Computers in Human Behavior, 2018 – Elsevier
… One of the most popular Cognitive Computing system is IBM Watson. On February 2011, it was introduced as a question-answering system based on advanced natural language processing, information retrieval, knowledge representation, and automated reasoning …

A novel classification method for paper-reviewer recommendation
S Zhao, D Zhang, Z Duan, J Chen, Y Zhang, J Tang – Scientometrics, 2018 – Springer
… Library Classification (CLC), we randomly select 152 papers, which are published in latest years and belongs to three subareas in TP (the field automation technology & computer technology) with respective CLC code TP181 (the subfield of Automatic reasoning & machine …

Big data and precision medicine: challenges and strategies with healthcare data
JM Kraus, L Lausser, P Kuhn, F Jobst, M Bock… – International Journal of …, 2018 – Springer
… fore ease the combination of distinct databases [62]. More complex approaches have then to be utilized for automatic reasoning, consistency checks and finally for the generation of new hypotheses [82]. 2.3 Data science … Write Question Answer A Answer Question Q A …

Kennislink Vakgebied Taalwetenschappen
OM van Koppen – Newsletter, 2018 – lotschool.nl
LOT. Sharing results, learning about high standard research, networking. Close …

Qualitative representations: How people reason and learn about the continuous world
KD Forbus – 2018 – books.google.com
Page 1. QUALITATIVE REPRESENTATIONS – — – º º t the Continuous World Page 2. Qualitative Representations Page 3. Page 4. Qualitative Representations How People Reason and Learn about the Continuous World Kenneth …

Learning Symbolic Latent Representations for Relational Data
H Blockeel – 2018 – lirias2repo.kuleuven.be
… Examples include problems of planning and scheduling, automated reasoning, theorem proving, robotics, language understanding and many … the world chess champion Gary Kasparov, Watson [46] which has defeated the top human players in the question-answering game of …

Spojité reprezentace v?t v neuronovém strojovém p?ekladu
O Cífka – 2018 – dspace.cuni.cz
… In contrast to continuous vector representations of sentences, logical forms are discrete objects of variable size (depending on the complexity of the represented sentence). They are well suited for automatic reasoning over a knowledge base …

Kennislink Vakgebied Taalwetenschappen
N Corver – Newsletter, 2018 – lotschool.nl
LOT. Sharing results, learning about high standard research, networking. Close …

A motivational model of BCI-controlled heuristic search
M Cavazza – Brain sciences, 2018 – mdpi.com
… and AI systems stems largely from the inability of humans to engage with, even less control, the automatic reasoning mechanisms underpinning AI … such as search-based planning, which has become the dominant planning technique [43], or question answering systems [44] of …

Kennislink Vakgebied Taalwetenschappen
OR d’Alessandro – Newsletter, 2018 – lotschool.nl
LOT. Sharing results, learning about high standard research, networking. Close …

Towards evaluation of cloud ontologies
MM Al-Sayed, HA Hassan, FA Omara – Journal of Parallel and Distributed …, 2018 – Elsevier
… such as Artificial Intelligence, Service Discovery, Knowledge Management, Semantic Web, Information Integration, Information Retrieval, Software Engineering, Cooperative Information systems, Electronic Commerce, Recommendation, Question Answering, and Information …

Environment Modeling-based Requirements Engineering for Software Intensive Systems
Z Jin – 2018 – books.google.com
Page 1. nts Engineering for Software Intensive Requireme 5= } ? |E NQ Environment Modeling-Based ) llllllll|º|TT ?. ??š —- WÊË |- Page 2. Environment Modeling-Based Requirements Engineering for Software Intensive Systems Page 3. This page intentionally left blank Page 4 …

An Ontology based Text-to-Picture Multimedia m-Learning System
AG Karkar – 2018 – qspace.qu.edu.qa
… conducted a survey about existing ontologies designed for educational use [18], and recent studies about question answering over linked data (QALD) [23]. We designed a knowledge base composed from an educational ontology that defines …

Beginning AI Bot Frameworks
M Biswas – Springer
Page 1. Beginning AI Bot Frameworks Getting Started with Bot Development — Manisha Biswas Page 2. Beginning AI Bot Frameworks Getting Started with Bot Development Manisha Biswas Page 3. Beginning AI Bot Frameworks: Getting Started with Bot Development …

Artificial Intelligence and the Two Singularities
C Chace – 2018 – books.google.com
Page 1. Chapman & Hall/CRC Artificial Intelligence and Robotics Series — ARTIFICIAL Wº N INTELLIGENCE º and fhe TW O º º SSINGULARITIES * – — orc press Tºrº. Frºntis ?irºup º, IHAP MARI ºr HALL B [III: Page 2. Artificial Intelligence and the Two Singularities Page 3 …

The Making of a New Science
G Ausiello – Springer
Page 1. Giorgio Ausiello The Making of a New Science A Personal Journey Through the Early Years of Theoretical Computer Science Page 2. The Making of a New Science Page 3. Giorgio Ausiello The Making of a New Science A Personal Journey Through the Early Years …

The Making of a New Science: A Personal Journey Through the Early Years of Theoretical Computer Science
G Ausiello – 2018 – books.google.com
Page 1. Giorgio Ausiello The Making of a New Science A Personal Journey Through the Early Years of Theoretical Computer Science Page 2. The Making of a New Science Page 3. Giorgio Ausiello The Making of a New Science …

A survey of sentiment analysis in social media
L Yue, W Chen, X Li, W Zuo, M Yin – Knowledge and Information Systems, 2018 – Springer
Page 1. Knowledge and Information Systems https://doi.org/10.1007/s10115-018-1236- 4 SURVEY PAPER A survey of sentiment analysis in social media Lin Yue1,2,3,5 · Weitong Chen3 · Xue Li3,4 · Wanli Zuo5 · Minghao Yin1,2,5 …