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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Intelligent language processing"

1

Zou, Xiao Hua. "The Study on the Framework of Intelligence Information Processing." Applied Mechanics and Materials 20-23 (January 2010): 861–66. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.861.

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It is proposed to get the fundamental theory of intelligent information processing with combining natural language understanding and computational intelligence. Considering applied fields on intelligent classification, indexing, retrieval, abstract and machine translation, natural language understanding can provide theoretical framework and computational intelligence will give technical realization.
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2

Tafazoli, Dara, Elena Gómez María, and Cristina A. Huertas Abril. "Intelligent Language Tutoring System." International Journal of Information and Communication Technology Education 15, no. 3 (July 2019): 60–74. http://dx.doi.org/10.4018/ijicte.2019070105.

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Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to learning by assuming the role of a real teacher/expert who adapts and steers the learning process according to the specific needs of each learner. This article reviews and discusses the issues surrounding the development and use of ITSs for language learning and teaching. First, the authors look at ICALL history: its evolution from CALL. Second, issues in ICALL research and integration will be discussed. Third, they will explain how artificial intelligence (AI) techniques are being implemented in language education as ITS and intelligent language tutoring systems (ITLS). Finally, the successful integration and development of ITLS will be explained in detail.
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3

Nagata, Noriko. "An Effective Application of Natural Language Processing in Second Language Instruction." CALICO Journal 13, no. 1 (January 14, 2013): 47–67. http://dx.doi.org/10.1558/cj.v13i1.47-67.

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This paper presents an intelligent CALI system called "Nihongo-CALI" (Japanese Computer Assisted Language Instruction), which employs natural language processing to provide immediate, grammatically sophisticated feedback to students in an interactive environment. Using this system, Nagata (1993) previously compared the effectiveness of the two different levels of computer feedback for teaching Japanese passive sentences: traditional feedback (which follows simple pattern-matching error analysis and indicates only missing/unexpected words in the learners' responses) and intelligent feedback (which utilizes a parsing technique to provide detailed grammatical explanations for the source of the learners' errors). The study found a statistically significant difference between traditional and intelligent feedback, favoring intelligent feedback. The present study compares the efficacy of intelligent CALI feedback with that of a more advanced, traditional CALI feedback (which also indicates the positions of missing particles in the learners' responses) for teaching basic sentence constructions in Japanese. The result indicates that the Intelligent CALI feedback is more effective than even the enhanced version of traditional CALI feedback, underscoring the importance of natural language processing technology in second language instruction.
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Pramada, Sawant. "Intelligent Sign Language Recognition Using Image Processing." IOSR Journal of Engineering 03, no. 02 (February 2013): 45–51. http://dx.doi.org/10.9790/3021-03224551.

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5

Pinto, David, Beatriz Beltrán, and Vivek Singh. "Recent advances in language & knowledge engineering." Journal of Intelligent & Fuzzy Systems 42, no. 5 (March 31, 2022): 4299–305. http://dx.doi.org/10.3233/jifs-219220.

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Language & Knowledge Engineering is essential for the successfully development of artificial intelligence. The technologies proposed in international forums are meant to improve all areas of our daily life whether it is related to production industries, social communities, government, education, or something else. We consider very important to reveal the recent advances Intelligent and Fuzzy Systems applied to Language & Knowledge Engineering because they are the base for the society of tomorrow. Thus, the aim of this special issue of Journal of Intelligent and Fuzzy Systems is to present a collection of papers that cover recent research results on the two wide topics: language and knowledge engineering. Even if the special issue is structured into these two general topics, we have covered specific themes such as the following ones: Natural Language Processing, Knowledge engineering, Pattern recognition, Artificial Intelligence and Language, Information Processing, Machine Learning Applied to Text Processing, Image and Text Classification, Multimodal data analysis, sentiment analysis, etc.
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Chen, Keliang, Yunxiao Zu, and Weizheng Ren. "Research and Design of Knowledge System Construction System Based on Natural Language Processing." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 12 (November 2019): 1959038. http://dx.doi.org/10.1142/s0218001419590389.

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The digital processing of content resources has subverted the traditional paper content processing model and has also spread widely. The digital resources processed by text structure need to be structured and processed by professional knowledge, which can be saved as a professional digital content resource of knowledge base and provide basic metadata for intelligent knowledge service platform. The professional domain-based knowledge system construction system platform explored in this study is designed based on natural language processing. Natural language processing is an important branch of artificial intelligence, which is the application of artificial intelligence technology in linguistics. The system first extracts the professional thesaurus and domain ontology in the digital resources and then uses the new word discovery algorithm based on the label weight designed by artificial intelligence technology to intelligently extract and clean the new words of the basic thesaurus. At the same time, the relationship system between knowledge points and elements is established to realize the association extraction of targeted knowledge points, and finally the output content is enriched from knowledge points into related knowledge systems. In order to improve the scalability and universality of the system, the extended architecture of the thesaurus, algorithms, computational capabilities, tags, and exception thesaurus was taken into account when designing. At the same time, the implementation of “artificial intelligence [Formula: see text] manual assistance” was adopted. On the basis of improving the system availability, the experimental basis of the optimization algorithm is provided. The results of this research will bring an artificial intelligence innovation after the digitization to the publishing industry and will transform the content service into an intelligent service based on the knowledge system.
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Shah, Rishabh, Siddhant Lahoti, and K. Lavanya. "An intelligent chat-bot using natural language processing." International Journal of Engineering Research 6, no. 5 (2017): 281. http://dx.doi.org/10.5958/2319-6890.2017.00019.8.

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Wei, Tan Chia, Mohd Hanafi Ahmad Hijazi, Suraya Alias, Ag Asri Ag Ibrahim, and Mohd Fairuz Iskandar Othman. "Intelligent Course Recommender Chatbot Using Natural Language Processing." International Journal on Advanced Science, Engineering and Information Technology 12, no. 5 (September 20, 2022): 1915. http://dx.doi.org/10.18517/ijaseit.12.5.14798.

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McSHANE, MARJORIE, and SERGEI NIRENBURG. "A KNOWLEDGE REPRESENTATION LANGUAGE FOR NATURAL LANGUAGE PROCESSING, SIMULATION AND REASONING." International Journal of Semantic Computing 06, no. 01 (March 2012): 3–23. http://dx.doi.org/10.1142/s1793351x12400016.

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OntoAgent is an environment that supports the cognitive modeling of societies of intelligent agents that emulate human beings. Like traditional intelligent agents, OntoAgent agents execute the core functionalities of perception, reasoning and action. Unlike most traditional agents, they engage in extensive "translation" functions in order to render perceived inputs into the unambiguous, ontologically-grounded knowledge representation language (KRL) that is used to model their knowledge, memory and reasoning. This paper describes the KRL of OntoAgent with a special focus on the many runtime functions used to translate between perceived inputs and the KRL, as well as to manipulate KRL structures for reasoning and simulation.
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10

Pikhart, Marcel. "Intelligent information processing for language education: The use of artificial intelligence in language learning apps." Procedia Computer Science 176 (2020): 1412–19. http://dx.doi.org/10.1016/j.procs.2020.09.151.

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Дисертації з теми "Intelligent language processing"

1

Lerjebo, Linus, and Johannes Hägglund. "Intelligent chatbot assistant: A study of Natural Language Processing and Artificial Intelligence." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42691.

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The development and research of Artificial Intelligence have had a recent surge in recent years, which includes the medical field. Despite the new technology and tools available, the staff is still under a heavy workload. The goal of this thesis is to analyze the possibilities of a chatbot whose purpose is to assist the medical staff and provide safety for the patients by guaranteeing that they are being monitored. With the use of technologies such as Artificial Intelligence, Natural Language Processing, and Voice Over Internet Protocol, the chatbot can communicate with the patient. It will work as an assistant for the working staff and provide the information from the calls to the medical staff. With the answers provided from the call, the staff will not be needing to ask routine questions every time and can provide help more quickly. The chatbot is administrated through a web application where administrators can initiate calls and add patients to the database.
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2

Huang, Qiang. "Speech and language processing for intelligent call routing." Thesis, University of East Anglia, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426693.

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3

Glinos, Demetrios George. "An intelligent editor for natural language processing of unrestricted text." Master's thesis, University of Central Florida, 1999. http://digital.library.ucf.edu/cdm/ref/collection/RTD/id/16913.

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University of Central Florida College of Arts and Sciences Thesis
The understanding of natural language by computational methods has been a continuing and elusive problem in artificial intelligence. In recent years there has been a resurgence in natural language processing research. Much of this work has been on empirical or corpus-based methods which use a data-driven approach to train systems on large amounts of real language data. Using corpus-based methods, the performance of part-of-speech (POS) taggers, which assign to the individual words of a sentence their appropriate part of speech category (e.g., noun, verb, preposition), now rivals human performance levels, achieving accuracies exceeding 95%. Such taggers have proved useful as preprocessors for such tasks as parsing, speech synthesis, and information retrieval. Parsing remains, however, a difficult problem, even with the benefit of POS tagging. Moveover, as sentence length increases, there is a corresponding combinatorial explosing of alternative possible parses. Consider the following sentence from a New York Times online article: After Salinas was arrested for murder in 1995 and lawyers for the bank had begun monitoring his accounts, his personal banker in New York quietly advised Salinas' wife to move the money elsewhere, apparently without the consent of the legal department. To facilite the parsing and other tasks, we would like to decompose this sentence into the following three shorter sentences which, taken together, convey the same meaning as the original: 1. Salinas was arrested for murder in 1995. 2. Lawyers for the bank had begun monitoring his accounts. 3. His personal banker in New York quietly adviced Salinas' wife to move the money elsewhere, apprently without the consent of the legal department. This study investigates the development of heuristics for decomposing such long sentences into sets of shorter sentences without affecting the meaning of the original sentences. Without parsing or semantic analysis, heuristic rules were developed based on: (1) the output of a POS tagger (Brill's tagger); (2) the punctuation contained in the input sentences; and (3) the words themselves. The heuristic algorithms were implemented in an intelligent editor program which first augmented the POS tags and assigned tags to punctuation, and then tested the rules against a corpus of 25 New York Times online articles containing approximately 1,200 sentences and over 32,000 words, with good results. Recommendations are made for improving the algorithms and for continuing this line of research.
M.S.;
Computer Science
Arts and Sciences
Computer Science;
220 p.
xii, 220 leaves, bound : ill. ; 28 cm.
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4

Amaral, Luiz Alexandre Mattos do. "Designing intelligent language tutoring systems for integration into foreign language instruction." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1179979688.

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Amaral, Luiz A. "Designing intelligent language tutoring systems for integration into foreign language instruction." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1179979688.

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Moiseeva, Alena [Verfasser], and Hinrich [Akademischer Betreuer] Schütze. "Statistical natural language processing methods for intelligent process automation / Alena Moiseeva ; Betreuer: Hinrich Schütze." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2020. http://d-nb.info/1218466944/34.

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Bailey, Stacey M. "Content Assessment in Intelligent Computer-aided Language Learning: Meaning Error Diagnosis for English as a Second Language." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1204556485.

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Sasa, Yuko. "Intelligence Socio-Affective pour un Robot : primitives langagières pour une interaction évolutive d'un robot de l’habitat intelligent." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM041/document.

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Анотація:
Le Traitement Automatique de la Parole (TAP) s’intéresse de plus en plus et progresse techniquement en matière d’étendue de vocabulaire, de gestion de complexité morphosyntaxique, de style et d’esthétique de la parole humaine. L’Affective Computing tend également à intégrer une dimension « émotionnelle » dans un objectif commun au TAP visant à désambiguïser le langage naturel et augmenter la naturalité de l’interaction personne-machine. Dans le cadre de la robotique sociale, cette interaction est modélisée dans des systèmes d’interaction, de dialogue, qui tendent à engendrer une dimension d’attachement dont les effets doivent être éthiquement et collectivement contrôlés. Or la dynamique du langage humain situé met à mal l’efficacité des systèmes automatiques. L’hypothèse de cette thèse propose dans la dynamique des interactions, il existerait une « glu socio-affective » qui ferait entrer en phases synchroniques deux individus dotés chacun d’un rôle social impliqué dans une situation/contexte d’interaction. Cette thèse s'intéresse à des dynamiques interactionnelles impliquant spécifiquement des processus altruistes, orthogonale à la dimension de dominance. Cette glu permettrait ainsi de véhiculer les événements langagiers entre les interlocuteurs, en modifiant constamment leur relation et leur rôle, qui eux même viennent à modifier cette glu, afin d’assurer la continuité de la communication. La seconde hypothèse propose que la glu socio-affective se construise à partir d’une « prosodie socio-affective pure » que l’on peut retrouver dans certaines formes de micro-expressions vocales. L’effet de ces événements langagiers serait alors graduel en fonction du degré de contrôle d’intentionnalité communicative qui s’observerait successivement par des primitives langagières : 1) des bruits de bouche (non phonétiques, non phonologiques), 2) des sons prélexicaux, 3) des interjections/onomatopées, 4) des imitations à contenu lexical contrôlé. Une méthodologie living-lab est ainsi développée au sein de la plateforme Domus, sur des boucles agiles et itératives co-construites avec les partenaires industriels et sociétaux. Un Magicien d’Oz – EmOz – est utilisé afin de contrôler les primitives vocales comme unique support langagier d’un robot majordome d’un habitat intelligent interagissant avec des personnes âgées en isolement relationnel. Un large corpus, EmOz Elderly Expressions –EEE– est ainsi recueilli. Cet isolement relationnel permet méthodologiquement d’appréhender les dimensions de la glu socio-affective, en introduisant une situation contrastive dégradée de la glu. Les effets des primitives permettraient alors d’observer les comportements de l’humain à travers des indices multimodaux. Les enjeux sociétaux abordés par la gérontechnologie montrent que l’isolement est un facteur de fragilisation où la qualité de la communication délite le maillage relationnel des personnes âgées alors que ces liens sont bénéfiques à sa santé et son bien-être. L’émergence de la robotique d’assistance en est une illustration. Le système automatisé qui découlera des données et des analyses de cette étude permettrait alors d’entraîner les personnes à solliciter pleinement leurs mécanismes de construction relationnelle, afin de redonner l’envie de communiquer avec leur entourage humain. Les analyses du corpus EEE recueilli montrent une évolution de la relation à travers différents indices interactionnels, temporellement organisés. Ces paramètres visent à être intégrés dans une perspective de système de dialogue incrémental – SASI. Les prémisses de ce système sont proposées dans un prototype de reconnaissance de la parole dont la robustesse ne dépendra pas de l’exactitude du contenu langagier reconnu, mais sur la reconnaissance du degré de glu, soit de l’état relationnel entre les locuteurs. Ainsi, les erreurs de reconnaissance tendraient à être compensées par l’intelligence socio-affective adaptative de ce système dont pourrait être doté le robot
The Natural Language Processing (NLP) has technically improved regarding human speech vocabulary extension, morphosyntax scope, style and aesthetic. Affective Computing also tends to integrate an “emotional” dimension with a common goal shared with NLP which is to disambiguate the natural language and increase the human-machine interaction naturalness. Within social robotics, the interaction is modelled in dialogue systems trying to reach out an attachment dimension which effects need to an ethical and collective control. However, the situated natural language dynamics is undermining the automated system’s efficiency, which is trying to respond with useful and suitable feedbacks. This thesis hypothesis supposes the existence of a “socio-affective glue” in every interaction, set up in between two individuals, each with a social role depending on a communication context. This glue is so the consequence of dynamics generated by a process which mechanisms rely on an altruistic dimension, but independent of dominance dimension as seen in emotions studies. This glue would allow the exchange of the language events between interlocutors, by regularly modifying their relation and their role, which is changing themselves this glue, to ensure the communication continuity. The second hypothesis proposes the glue as built by “socio-affective pure prosody” forms that enable this relational construction. These cues are supposed to be carried by hearable and visible micro-expressions. The interaction events effect would also be gradual following the degree of the communication’s intentionality control. The graduation will be continuous through language primitives as 1) mouth noises (neither phonetics nor phonological sounds), 2) pre-lexicalised sounds, 3) interjections and onomatopoeias, 4) controlled command-based imitations with the same socio-affective prosody supposed to create and modify the glue. Within the Domus platform, we developed an almost living-lab methodology. It functions on agile and iterative loops co-constructed with industrial and societal partners. A wizard of oz approach – EmOz – is used to control the vocal primitives proposed as the only language tools of a Smart Home butler robot interacting with relationally isolated elderly. The relational isolation allows the dimensions the socio-affective glue in a contrastive situation where it is damaged. We could thus observe the primitives’ effects through multimodal language cues. One of the gerontechnology social motivation showed the isolation to be a phenomenon amplifying the frailty so can attest the emergence of assistive robotics. A vicious circle leads by the elderly communicational characteristics convey them to some difficulties to maintain their relational tissue while their bonds are beneficial for their health and well-being. If the proposed primitives could have a real effect on the glue, the automated system will be able to train the persons to regain some unfit mechanisms underlying their relational construction, and so possibly increase their desire to communicate with their human social surroundings. The results from the collected EEE corpus show the relation changes through various interactional cues, temporally organised. These denoted parameters tend to build an incremental dialogue system in perspectives – SASI. The first steps moving towards this system reside on a speech recognition prototype which robustness is not based on the accuracy of the recognised language content but on the possibility to identify the glue degree (i.e. the relational state) between the interlocutors. Thus, the recognition errors avoid the system to be rejected by the user, by tempting to be balanced by this system’s adaptive socio-affective intelligence
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Wärmegård, Erik. "Intelligent chatbot assistant: A study of integration with VOIP and Artificial Intelligence." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42693.

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Development and research on Artificial Intelligence have increased during recent years, and the field of medicine is not excluded as a target audience for this top modern technology. Despite new research and tools in favor of medical care, the staff is still under heavy workloads. The goal of this thesis is to analyze and propose the possibility of a chatbot that aims to ease the pressure on the medical staff. To provide a guarantee that patients are being monitored. With Artificial Intelligence, VOIP, Natural Language Processing, and web development, this chatbot can communicate with a patient, which will act as an assistant tool that conducts preparatory work for the medical staff. The system of the chatbot is integrated through a web application where the administrator can initiate call and store clients onto the database. To ascertain that the system operates in real-time, several tests have been carried out to tests concerning the latency between subsystems and the quality of service.
I utvecklingen av intelligenta system har sjukvården etablerat sig som en stor målgrupp. Trots avancerade tekniker så är sjukvården fortfarande under tung belastning. Målet för detta examensarbete är att undersöka möjligheten av en chatbot vars syfte är att lätta på arbetsbelastningen hos sjukvårdspersonalen och samtidigt erbjuda en garanti för att patienter får den tillsyn och återkoppling de behöver. Med hjälp av Artificiell Intelligens, VOIP, Natural Language Processing och webbutveckling kan denna chatbot kommunicera med patienten. Chatboten agerar som ett assisterande verktyg som står för ett förarbete i beslutstagandet för sjukvårdspersonal. Ett systemsom inte bara ger praktisk nytta utan också ett främjande av den utveckling som Artificiell Intelligens gör inom sjukvården. Systemet administreras genom en hemsida som kopplar samman de flera olika komponenterna. Här kan en administratör initiera samtal och spara klienter som ska ringas till databasen. För att kunna fastställa att systemet opererar i realtid har görs flertalet prestandatester avseende både tidsfördröjningar och samtalskvalité.
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Kauppi, Ilkka. "Intermediate language for mobile robots : a link between the high-level planner and low-level services in robots /." Espoo [Finland] : VTT Technical Research Centre of Finland, 2003. http://www.vtt.fi/inf/pdf/publications/2003/P510.pdf.

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Книги з теми "Intelligent language processing"

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Kłopotek, Mieczysław A., Jacek Koronacki, Małgorzata Marciniak, Agnieszka Mykowiecka, and Sławomir T. Wierzchoń, eds. Language Processing and Intelligent Information Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38634-3.

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Shaalan, Khaled, Aboul Ella Hassanien, and Fahmy Tolba, eds. Intelligent Natural Language Processing: Trends and Applications. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67056-0.

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3

Batchelor, Bruce G. Intelligent image processing in Prolog. London: Springer-Verlag, 1991.

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4

Batchelor, Bruce G. Intelligent Image Processing in Prolog. London: Springer London, 1991.

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5

Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning. Beijing: O’Reilly Media, 2019.

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6

Theeramunkong, Thanaruk, Rachada Kongkachandra, Mahasak Ketcham, Narit Hnoohom, Pokpong Songmuang, Thepchai Supnithi, and Kiyota Hashimoto, eds. Advances in Intelligent Informatics, Smart Technology and Natural Language Processing. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-94703-7.

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Theeramunkong, Thanaruk, Rachada Kongkachandra, and Thepchai Supnithi, eds. Advances in Natural Language Processing, Intelligent Informatics and Smart Technology. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70016-8.

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8

Williams, Noel. The intelligent micro: Artificial intelligence for microcomputers. London: McGraw-Hill, 1985.

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9

Kevitt, Paul Mc. Integration of Natural Language and Vision Processing: (Volume II) Intelligent Multimedia. Dordrecht: Springer Netherlands, 1995.

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10

Pei, Zheng. Linguistic Values Based Intelligent Information Processing: Theory, Methods, and Applications. Paris: Atlantis Press, 2010.

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Частини книг з теми "Intelligent language processing"

1

Kacalak, Wojciech, Keith Douglas Stuart, and Maciej Majewski. "Intelligent Natural Language Processing." In Lecture Notes in Computer Science, 584–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_79.

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2

Brill, Eric. "Processing Natural Language without Natural Language Processing." In Computational Linguistics and Intelligent Text Processing, 360–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36456-0_37.

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Verma, Brijesh, Hong Lee, and John Zakos. "An Automatic Intelligent Language Classifier." In Advances in Neuro-Information Processing, 639–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03040-6_78.

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Batchelor, Bruce G. "Extending the Language." In Intelligent Image Processing in Prolog, 101–26. London: Springer London, 1991. http://dx.doi.org/10.1007/978-1-4471-0401-8_4.

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Ying, Shi. "Research on Semantic Programming Language." In Intelligent Information Processing VI, 15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32891-6_5.

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Majewski, Maciej, and Wojciech Kacalak. "Intelligent System for Natural Language Processing." In Lecture Notes in Computer Science, 742–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-37275-2_93.

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Niiranen, Samuli, Jari Yli-Hietanen, and Olli Yli-Harja. "Natural Language and Biological Information Processing." In Intelligent Systems Reference Library, 219–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19621-8_10.

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Fenstad, Jens Erik, and Jan Tore Lønning. "Computational semantics: Steps towards “intelligent” text processing." In Natural Language and Logic, 70–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-53082-7_18.

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de Novais, Eder Miranda, Ivandré Paraboni, and Diogo Takaki Ferreira. "Highly-Inflected Language Generation Using Factored Language Models." In Computational Linguistics and Intelligent Text Processing, 429–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19400-9_34.

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Mihalcea, Rada, Hugo Liu, and Henry Lieberman. "NLP (Natural Language Processing) for NLP (Natural Language Programming)." In Computational Linguistics and Intelligent Text Processing, 319–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11671299_34.

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Тези доповідей конференцій з теми "Intelligent language processing"

1

Kumar, Rashi, and Vineet Sahula. "Intelligent Approaches for Natural Language Processing for Indic Languages." In 2021 IEEE International Symposium on Smart Electronic Systems (iSES). IEEE, 2021. http://dx.doi.org/10.1109/ises52644.2021.00084.

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2

Gelbukh, A. "Natural language processing." In Fifth International Conference on Hybrid Intelligent Systems (HIS'05). IEEE, 2005. http://dx.doi.org/10.1109/ichis.2005.79.

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Doszkocs, Tamas. "Natural language processing in intelligent information retrieval." In the 1985 ACM annual conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/320435.320541.

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"Session: Natural Language Processing." In 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2019. http://dx.doi.org/10.1109/iccp48234.2019.8959560.

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Gupta, Prashant, Aman Goswami, Sahil Koul, and Kashinath Sartape. "IQS-intelligent querying system using natural language processing." In 2017 International Conference of Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2017. http://dx.doi.org/10.1109/iceca.2017.8212846.

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K, Vindhya Vasini, Tejasvi K, Pravallika K, and Ch Nanda Krishna. "A Natural Language Processing based Intelligent Bot Application." In 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, 2022. http://dx.doi.org/10.1109/icscds53736.2022.9760998.

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Song, Peiyou, Anhei Shu, David Phipps, Mohit Tiwari, Dan S. Wallach, Jedidiah R. Crandall, and George F. Luger. "Language without words: A pointillist model for natural language processing." In 2012 Joint 6th Intl. Conference on Soft Computing and Intelligent Systems (SCIS) and 13th Intl. Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2012. http://dx.doi.org/10.1109/scis-isis.2012.6505413.

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Ahirrao, Mayur, Yash Joshi, Atharva Gandhe, Sumeet Kotgire, and Rohini G. Deshmukh. "Phrase Composing Tool using Natural Language Processing." In 2021 International Conference on Intelligent Technologies (CONIT). IEEE, 2021. http://dx.doi.org/10.1109/conit51480.2021.9498546.

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Yasaswi, K., Vijaya Kumar Kambala, P. Sai Pavan, M. Sreya, and V. Jasmika. "News Classification using Natural Language Processing." In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM). IEEE, 2022. http://dx.doi.org/10.1109/iciem54221.2022.9853174.

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Mantegh, Iraj, and Nazanin S. Darbandi. "Knowledge-Based Task Planning Using Natural Language Processing for Robotic Manufacturing." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-29123.

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Анотація:
Robotic alternative to many manual operations falls short in application due to the difficulties in capturing the manual skill of an expert operator. One of the main problems to be solved if robots are to become flexible enough for various manufacturing needs is that of end-user programming. An end-user with little or no technical expertise in robotics area needs to be able to efficiently communicate its manufacturing task to the robot. This paper proposes a new method for robot task planning using some concepts of Artificial Intelligence. Our method is based on a hierarchical knowledge representation and propositional logic, which allows an expert user to incrementally integrate process and geometric parameters with the robot commands. The objective is to provide an intelligent and programmable agent such as a robot with a knowledge base about the attributes of human behaviors in order to facilitate the commanding process. The focus of this work is on robot programming for manufacturing applications. Industrial manipulators work with low level programming languages. This work presents a new method based on Natural Language Processing (NLP) that allows a user to generate robot programs using natural language lexicon and task information. This will enable a manufacturing operator (for example for painting) who may be unfamiliar with robot programming to easily employ the agent for the manufacturing tasks.
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Звіти організацій з теми "Intelligent language processing"

1

Li, Eliot, Charles Nicholas, Tim Oates, and Raman K. Mehra. Intelligent Record Linkage Techniques Based on Information Retrieval, Natural Language Processing, and Machine Learning. Fort Belvoir, VA: Defense Technical Information Center, November 2002. http://dx.doi.org/10.21236/ada408937.

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2

Murdick, Dewey, Daniel Chou, Ryan Fedasiuk, and Emily Weinstein. The Public AI Research Portfolio of China’s Security Forces. Center for Security and Emerging Technology, March 2021. http://dx.doi.org/10.51593/20200057.

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Анотація:
New analytic tools are used in this data brief to explore the public artificial intelligence (AI) research portfolio of China’s security forces. The methods contextualize Chinese-language scholarly papers that claim a direct working affiliation with components of the Ministry of Public Security, People's Armed Police Force, and People’s Liberation Army. The authors review potential uses of computer vision, robotics, natural language processing and general AI research.
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