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检索条件"任意字段=7th International Conference on Advanced Language Processing and Web Information Technology"

共 1371 条记录，以下是81-90 订阅

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Based on Forward Reference Object Transaction identification Algorithm on web mining

Based on Forward Reference Object Transaction identification...

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6th international conference on advanced language processing and web information technology

作者： Chen, Li Li, Zhishu Ju, Shenggen Sichuan Univ Dept Comp Chengdu 610064 Peoples R China

ISBN: (纸本)9780769529301

this paper puts forward a new transaction identification algorithm (TIFRO) in web mining, which is based on forward reference object. Firstly, TIFRO uses the maximal forward reference algorithm (MFR) to get the forward reference path, and then join a final object of the forward reference path to transaction set. Secondly, TIFRO starts a new transaction by judging the reference length (RL) in case of RL is longer than the maximal reference length(T-MAX). So TYRO can find the object set but not the path set of MFR. thirdly, TIFRO uses SPADE algorithm to discovery frequency patterns. Finally, we compare TIFRO with MFR in performance.

关键词： forward reference object(FRO) transaction identification Maximal Forward Reference(MFR) web mining SPADE

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WikiKreator: Improving Wikipedia Stubs Automatically 53

WikiKreator: Improving Wikipedia Stubs Automatically

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53rd Annual Meeting of the Association-for-Computational-Linguistics (ACS) / 7th international Joint conference on Natural language processing of the Asian-Federation-of-Natural-language-processing (IJCNLP)

作者： Banerjee, Siddhartha Mitra, Prasenjit Penn State Univ Informat Sci & Technol University Pk PA 16802 USA Hamad Bin Khalifa Univ Qatar Comp Res Inst Doha Qatar

ISBN: (纸本)9781941643723

Stubs on Wikipedia often lack comprehensive information. the huge cost of editing Wikipedia and the presence of only a limited number of active contributors curb the consistent growth of Wikipedia. In this work, we present WikiKreator, a system that is capable of generating content automatically to improve existing stubs on Wikipedia. the system has two components. First, a text classifier built using topic distribution vectors is used to assign content from the web to various sections on a Wikipedia article. Second, we propose a novel abstractive summarization technique based on an optimization framework that generates section-specific summaries for Wikipedia stubs. Experiments show that WikiKreator is capable of generating well-formed informative content. Further, automatically generated content from our system have been appended to Wikipedia stubs and the content has been retained successfully proving the effectiveness of our approach.

关键词： Classification (of information)

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New Tools for web-Scale N-grams 7

New Tools for Web-Scale N-grams

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7th international conference on language Resources and Evaluation (LREC)

作者： Lin, Dekang Church, Kenneth Ji, Heng Sekine, Satoshi Yarowsky, David Bergsma, Shane Patil, Kailash Pitler, Emily Lathbury, Rachel Rao, Vikram Dalwani, Kapil Narsale, Sushant Univ Alberta Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9782951740860

While the web provides a fantastic linguistic resource, collecting and processing data at web-scale is beyond the reach of most academic laboratories. Previous research has relied on search engines to collect online information, but this is hopelessly inefficient for building large-scale linguistic resources, such as lists of named-entity types or clusters of distributionally-similar words. An alternative to processing web-scale text directly is to use the information provided in an N-gram corpus. An N-gram corpus is an efficient compression of large amounts of text. An N-gram corpus states how often each sequence of words (up to length N) occurs. We propose tools for working with enhanced web-scale N-gram corpora that include richer levels of source annotation, such as part-of-speech tags. We describe a new set of search tools that make use of these tags, and collectively lower the barrier for lexical learning and ambiguity resolution at web-scale. the tools will allow novel sources of information to be applied to long-standing natural language challenges.

关键词： Search engines

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Building BIS/BMS with wireless communication system in Korea

Building BIS/BMS with wireless communication system in Korea

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6th international conference on advanced language processing and web information technology

作者： Kim, Bong Gyun Sirn, Yong Ho Ahn, Seon Hong Chu, Kyung Tae Lee, Bong Gyou Strategy Planning Office Team Investment Management Dept. KT Corporation Graduate School of Information Yonsei University

ISBN: (纸本)9780769529301

the purpose of this paper is to provide a forecast model and policy guideline for setting selection criteria for a wireless communications system, a crucial technology in BIS and BMS according to Korean case studies. Existing cases were used for reference, and a combination of tracking method and communication method was used to construct the forecast models. Each model was rated for its advantages and disadvantages, as well as selection criteria, which resulted in a policy guideline applicable to local authorities in Korea or cities overseas that are considering the introduction of BIS in their respective regions.

关键词： BIS(Bus information system) BMS(Bus management system) wireless communications traffic system ubiquitous

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ML-based failure detection approach for predictive maintenance in an industry 4.0 oriented web manufacturing control application 7

ML-based failure detection approach for predictive maintenan...

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IEEE 7th international conference on advanced Technologies, Signal and Image processing (ATSIP)

作者： Smaoui, Sirine Baklouti, Mouna Univ Sfax Natl Engn Sch Sfax CES Lab Sfax Tunisia

ISBN: (纸本)9798350351491;9798350351484

With the increasing reach of Industry 4.0, the Internet of things (IoT) and Artificial Intelligence (AI) and many other technologies, have emerged as pivotal components in the era of information technology. Recent progress in AI, and its sub-field machine learning (ML), have influenced numerous research domains inside the industry, achieving improvements that were not possible with conventional optimization techniques, notably illustrated in the case of predictive maintenance. A significant component of predictive maintenance is fault detection. the goal of predictive maintenance is to avoid future machine failure and consequent downtime by anticipating faults in machinery. As a result, the aim of this research is to employ ML models for fault identification process. A concrete dataset was employed with real sensors' outputs allowing to make analysis of faults in machines mounted with various types of sensors. Four distinct supervised ML algorithms were applied in our work in which their hyper-parameters were tuned with both Grid Search and Random Search methods. A comparative study between the algorithms' performances was made in order to select the best one with highest metrics percentages. A web-based application was also developed, to monitor data and send alerts when detecting anomalies either via SMS, email or inside the provided web interface.

关键词： Industry 4.0 IoT AI ML Predictive Maintenance Fault Detection Grid Search Random Search web Application

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Cross-Domain Semantic web Model for Understanding Multilingual Natural language Queries: English/Arabic Health/Food Domain Use Case 7

Cross-Domain Semantic Web Model for Understanding Multilingu...

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7th international conference on Ambient Systems, Networks and Technologies (ANT) / 6th international conference on Sustainable Energy information technology (SEIT)

作者： Al-Nazer, Ahmed Albukhitan, Saeed Helmy, Tarek King Fahd Univ Petr & Minerals Informat & Comp Sci Dept Coll Comp Sci & Engn Mail Box 413 Dhahran 31216 Saudi Arabia

With the growth of the Semantic web and its applications, the need to use it in different languages, such as Arabic, is becoming more important. Two of the challenges with the Semantic web technologies are the lack of multilingual support and the complexity of integrating multiple ontologies used by this technology. the objective of this paper is to present efforts that will help users who use the Arabic language to ask natural language questions and then get their semantic representation in SPARQL that allows them to be executed and get the relevant semantic results. this natural language interface makes more use of the cross-domain ontologies and hence improves the understanding of their inquiries, which is needed in some critical domains such as health and food where precise advice is essential. the approach we followed is multilingual and overcomes the limitations in the published relevant systems. With the proposed approach, users who speak Arabic can use the widely published ontologies in English without concern for the translation of their questions. the proposed approach will take care of matching the entered questions with the relevant ontologies to produce their semantic web queries. the proposed approach has been implemented and empirically evaluated. the experimental results are promising, which will help in improving the awareness and usage of the Semantic web by different lingual and cultural users. (C) 2016 the Authors. Published by Elsevier B.V.

关键词： Semantic web SPARQL Arabic Natural language Question Answering Semantic web Service

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Natural language processing based Question Answering Techniques: A Survey 7

Natural Language Processing based Question Answering Techniq...

引用

7th IEEE international conference on Engineering Technologies and Applied Sciences, ICETAS 2020

作者： Arbaaeen, Ammar Shah, Asadullah International Islamic University Malaysia Faculty of Information and Communication Technology Department of Computer Science Kuala Lumpur Malaysia International Islamic University Malaysia Faculty of Information and Communication Technology Kuala Lumpur Malaysia

ISBN: (纸本)9780738105048

the rapid development in the field of information science and the increase in the usage of information retrieval strategies have empowered users to retrieve more accurate information. the availability of information in a different format and across different has presented colossal difficulties for information retrieval using information retrieval techniques. In this paper, an attempt is made at highlighting the question and answering (QA) systems that provide users the platform to express their question using the Natural language and also retrieve the response from such systems in Natural language. the four important modules of any QA system are the Natural language Question (NLQ) processing, document processing, passage processing, and answer processing. Fundamentally, most QA systems combined several techniques from other fields such as information retrieval, knowledge representation, and natural language processing to process NLQ and present the most insightful response based on the stored document. this paper gives a thorough review of the various survey on the QA systems frameworks, their methodologies, types, approaches, and challenges of QA systems. © 2020 IEEE.

关键词： information retrieval

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FIDJI: web Question-Answering at Quaero 2009 7

FIDJI: Web Question-Answering at Quaero 2009

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7th international conference on language Resources and Evaluation (LREC)

作者： Tannier, Xavier Moriceau, Veronique Univ Paris 11 CNRS LIMSI F-91403 Orsay France

ISBN: (纸本)9782951740860

this paper presents the participation of FIDJI system to the web Question-Answering evaluation campaign organized by Quaero in 2009. FIDJI is an open-domain question-answering system which combines syntactic information with traditional QA techniques such as named entity recognition and term weighting in order to validate answers through multiple documents. It was originally designed to process "clean" document collections. Overall results are significantly lower than in traditional campaigns but results (for French evaluation) are quite good compared to other state-of-the-art systems. they show that a syntax-based strategy, applied on uncleaned web data, can still obtain good results. Moreover, we obtain much higher scores on "complex" questions, i.e. 'how' and 'why' questions, which are more representative of real user needs. these results show that questioning the web with advanced linguistic techniques can be done without heavy pre-processing and with results that come near to best systems that use strong resources and large structured indexes.

关键词： Syntactics

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A multilayered bilingual word-alignment algorithm

A multilayered bilingual word-alignment algorithm

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6th international conference on advanced language processing and web information technology

作者： Zhang Ke-liang Zhang Xiao-Fei Huang He-Yan Nanjing Univ Sci & Technol Nanjing 210094 Peoples R China Chinese Acad Sci Res Ctr Comp & Language Informat Engn Beijing 100089 Peoples R China Luoyang Univ Foreign Languages Luoyang 471003 Peoples R China

ISBN: (纸本)9780769529301

Bilingual word alignment is to find the corresponding word-level translation between the source and the target language sentences. It is widely used in the area of natural language processing, like machine translation, cross-language information retrieval, bilingual dictionary compilation. However, bilingual word alignment is a very difficult task involving many challenges such as morphology, syntax, semantics, human translation habits, and the inherent difference between English and Chinese. In this paper, a new algorithm is proposed By adopting a multilayered matching and disambiguation strategy, the bilingual word-alignment task is transformed to an iterative solution of anchor word-pair. the positive experimental results of 93.5% precision, 77.3% recall, and 84.2% F-score show the algorithm's effectiveness.

关键词： information retrieval iterative solution Natural language processing Word Object oriented programming languages English English language machine translation algorithms syntax Dictionaries as Topic

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A hybrid genetic and particle swarm algorithm for service composition

A hybrid genetic and particle swarm algorithm for service co...

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6th international conference on advanced language processing and web information technology

作者： Liu, Jian Li, Jun'e Liu, Kaipei Wei, Wen Wuhan Univ Sch Elect Engn Wuhan 430072 Peoples R China Wuhan Univ Ctr Comp Wuhan 430072 Peoples R China Wuhan Municipal Meter Elect Polytech Sch Wuhan Peoples R China

ISBN: (纸本)9780769529301

web Service Composition (WSC) has become a hotspot in recent research. Current solutions focus on ontology information representation and ontology based web service matching, which lacks flexibility. From simulation of human cognision, this paper proposed a hybrid Genetic Particle Swarm Algorithm (GPSA) to solve the problem of WSC, which is a Multi-Objective Problem (MOP). Genetic Algorithm (GA) is used to search throughout the problem space, and Particle Swarm Optimization (PSO) is used to enhance local search ability. PSO can reduce the calculation cost by trimming useless braches. Feedback information is used to decide how to balance GA and PSO, which means how to balance global and local optimization. Experiments show that GPSA can solve WSC Problem (WSCP) and balance between global and local optimization.

关键词： web service composition particle swarm algorithm genetic algorithm multi-objective problem

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