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7th language and technology conference: Human language Technologies as a Challenge for Computer Science and Linguistics, LTC 2015

7th Language and Technology Conference: Human Language Techn...

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7th language and technology conference: Human language Technologies as a Challenge for Computer Science and Linguistics, LTC 2015

ISBN: (纸本)9783319937816

the proceedings contain 31 papers. the special focus in this conference is on Human language Technologies as a Challenge for Computer Science and Linguistics. the topics include: Multilingual tokenization and part-of-speech tagging. Lightweight versus heavyweight algorithms;a semantic similarity measurement tool for wordnet-like databases;similarity measure for polish short texts based on wordnet-enhanced bag-of-words representation;methods of linking linguistic resources for semantic role labeling;a quality estimation system for hungarian;Leveraging the advantages of associative alignment methods for PB-SMT systems;events extractor for polish based on semantics-driven extraction templates;understanding questions and extracting answers: Interactive quiz game application design;exploiting wikipedia-based information-rich taxonomy for extracting location, creator and membership related information for conceptnet expansion;neural networks revisited for proper name retrieval from diachronic documents;lexical analysis of serbian with conditional random fields and large-coverage finite-state resources;improving chunker performance using a web-based semi-automatic training data analysis tool;a Connectionist Model of Reading with Error Correction Properties;the Automatic Generation of Nonwords for Lexical Recognition Tests;teaching Words in Context: Code-Switching Method for English and Japanese Vocabulary Acquisition Systems;automatic Extraction of Harmful Sentence Patterns with Application in Cyberbullying Detection;sentiment Analysis in Polish web-Political Discussions;saturation Tests in Application to Validation of Opinion Corpora: A Tool for Corpora processing;Issues and Challenges in Developing Statistical POS Taggers for Sambalpuri;cross-Linguistic Projection for French-Vietnamese Named Entity Translation;cross-Lingual Adaptation of Broadcast Transcription System to Polish language Using Public Data Sources;National language Technologies Portals for LRLs: A Case Stu

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Intelligent AI Assisted Psychological Disorder Analysis Using Sentiment Inference 7

Intelligent AI Assisted Psychological Disorder Analysis Usin...

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7th international conference on Advances in Computing, Communications and Informatics, ICACCI 2018

作者： Kamath, Anil Raje, Nirav Konduri, Saishashank Shah, Hardik Naik, Varsha Bhattacharjee, Krishnanjan Shivakarthik Mehta, Swati Kumar, Ajai Department of Information Technology Maharashtra Institute of Technology Pune India Applied AI Group C-DAC Pune India

ISBN: (纸本)9781538653142

In the current scenario, there is no computing system in practice which understands or provides analytical insights for the language used in the psychological documents maintained by psychiatrists. Most importantly, there is no standardized language or methodology used in psychiatric practice to diagnose a psychological disorder. the main aim of our system is to provide a standardized platform for an assistance in diagnosis using Natural language processing techniques and Sentiment Inference. the system would suggest to the psychiatrist, the psychological disorder identified and its severity from the document text. the severity is obtained via a gradient score, which is computed by the semantic based gradient processing module - the core of our research. the psychiatrist can approve/correct the system diagnosis if necessary and reassign the gradient values for phrases contributing towards disorder severity. In an automated process, model gets re-trained after a particular threshold is reached, continually improving its performance. © 2018 IEEE.

关键词： Machine learning

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Ar-SLoTE: A Recognizing Textual Entailment Tool for Arabic Question/Answering Systems

Ar-SLoTE: A Recognizing Textual Entailment Tool for Arabic Q...

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international conference on information and Communication technology and Accessibility (ICTA)

作者： Mabrouka Ben-Sghaier Wided Bakari Mahmoud Neji Faculty of Economics and Management MIR@CL Sfax Tunisia

ISBN: (数字)9781728161839

ISBN: (纸本)9781728161846

Recognizing the relation of entailment between sentences is an important and common part of linguistic communication. the recognizing textual entailment task has been proposed as a solution for this problem. In this paper, we present an Arabic Recognizing Textual Entailment Tool called Ar-SLoTE "Arabic Semantic Logical Textual Entailment Tool". the proposed tool is composed of five modules: pretreatment, linguistic analysis, first-order logic representation, features extraction and entailment decision modules. It extracts the logical representations of the hypothesis/text pairs in order to extract valuable and informative features namely, predicates-arguments overlap, semantic similarity and named entity matching. Ar-SLoTE is destined especially to Arabic factual question/answering systems and the attained result is very encouraging.

关键词： Semantics Feature extraction Tools Linguistics Task analysis Natural language processing

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Multi-turn Inference Matching Network for Natural language Inference 7th

Multi-turn Inference Matching Network for Natural Language I...

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7th CCF international conference on Natural language processing and Chinese Computing, NLPCC

作者： Liu, Chunhua Jiang, Shan Yu, Hainan Yu, Dong Beijing Language & Culture Univ Beijing Peoples R China Beijing Adv Innovat Language Resources BLCU Beijing Peoples R China

ISBN: (纸本)9783319995014;9783319995007

Natural language Inference (NLI) is a fundamental and challenging task in Natural language processing (NLP). Most existing methods only apply one-pass inference process on a mixed matching feature, which is a concatenation of different matching features between a premise and a hypothesis. In this paper, we propose a new model called Multiturn Inference Matching Network (MIMN) to perform multi-turn inference on different matching features. In each turn, the model focuses on one particular matching feature instead of the mixed matching feature. To enhance the interaction between different matching features, a memory component is employed to store the history inference information. the inference of each turn is performed on the current matching feature and the memory. We conduct experiments on three different NLI datasets. the experimental results show that our model outperforms or achieves the state-of-the-art performance on all the three datasets.

关键词： Natural language Inference Multi-turn inference Memory mechanism

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Development of semantic web application architecture for natural language based querying 7

Development of semantic web application architecture for nat...

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7th Turkish National Software Architecture conference, UYMK 2018

作者： Tasar, Ceren Ocal Komesli, Murat Unalir, Murat Osman Yasar University Software Engineering Department Universite Cad. 35 Bornova Izmir35100 Turkey Yasar University Management Information Systems Department Universite Cad. 35 Bornova Izmir35100 Turkey Ege University Computer Engineering Department Universite Cad. 9 BornovaIzmir35100 Turkey

With the developing technology and increased demand on practical usage of knowledge, users require to interact with systems by using natural language. Researchers discover the necessity of natural language queries should be converted to machine understandable format to meet the requirement of users. the necessity of the conversion triggered the researches on studies on question answering systems that is one of the systems mostly interact with natural language queries. For question answering systems that utilizes structural knowledge sources, understanding user intention accurately consists of the processes of natural language processing, representing the user intention and forming structured query to generate the answer. A technique and an architecture to convert natural language query to ontology query language by utilizing from both linguistic and semantic technologies are proposed in this study. Automatic conversion of an unstructured natural language query to a structured ontology query language SPARQL and process of producing answer over linked data are explained in the proposed technique and architecture. A different approach other than the related studies is followed in terms of defining a "Query Semantization" layer in the proposed architecture and developing a natural language aware ontology for the technique proposed. Contribution to the literature is expected by combining natural language processing technique and semantic web technologies with a different approach. © 2019 CEUR Workshop *** Rights Reserved.

关键词： Ontology

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Parsing of Polish in Graph Database Environment 7th

Parsing of Polish in Graph Database Environment

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7th language and technology conference: Human language Technologies as a Challenge for Computer Science and Linguistics, LTC 2015

作者： Posiadala, Jan Czaja, Hubert Szczechla, Eliza Susicki, Pawel Scott Tiger S.A. 15 Kolektorska Street Warsaw Poland

ISBN: (纸本)9783319937816

this paper describes the basic concepts and features of the Langusta system. Langusta is a natural language processing environment embedded in a graph database. the paper presents a rule-based syntactic parsing system for the Polish language using various linguistic resources, including those containing semantic information. the advantages of this approach are directly related to the deployment of the graph paradigm, in particular to the assumption, that rules describing the syntax of the Polish language are valid queries in a graph database query language (Cypher). © 2018, Springer international Publishing AG, part of Springer Nature.

关键词： Natural language processing systems

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LeadsRobot: A Sales Leads Generation Robot Based on Big Data Analytics 7th

LeadsRobot: A Sales Leads Generation Robot Based on Big Data...

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7th international Congress on Big Data (BigData Congress) Held as Part of the Services conference Federation (SCF)

作者： Zeng, Jing Che, Jin Xing, Chunxiao Zhang, Liang-Jie Tsinghua Univ Res Inst Web Informat Beijing Peoples R China Kingdee Int Software Inc Shenzhen Peoples R China Natl Engn Res Ctr Supporting Software Enterprise Shenzhen Peoples R China

ISBN: (纸本)9783319943015;9783319943008

Sale leads are the essential concern of salesman and marketing staffs, who may seek them in blindly searching by using search engine in a substantial of online information. Unfortunately, it is tricky to extract useful and valuable leads from such huge online data. To address this issue, in this paper, we present a leads generation robot-LeadsRobot, which is a software enabled robot. It can intelligently understand the requirements of leads for salesman and then automatically mine the leads from web big data to recommend them to salesman. A robot architecture is devised with service based technologies, it can accomplish the automatic understanding, crawling, analysis and recommendation. To achieve the task, we use automatic web crawling to gain the raw data from web data. Natural language processing is employed for extract leads from them, then intelligence recommendation is proceeded for salesman via word2vec based text analysis. Finally we demonstrate our proposed robot in a real application case and evaluate performance of system to show its efficiency and effectiveness.

关键词： Sale leads NLP Big data Robot

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Improving chunker performance using a web-based semi-automatic training data analysis tool 7th

Improving chunker performance using a web-based semi-automat...

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7th language and technology conference: Human language Technologies as a Challenge for Computer Science and Linguistics, LTC 2015

作者： Endrédy, István Faculty of Information Technology and Bionics MTA-PPKE Hungarian Language Technology Research Group Pázmány Péter Catholic University 50/a Práter Street Budapest1083 Hungary

ISBN: (纸本)9783319937816

Fine tuning features for NP chunking is a difficult task. the effects of a modification are sometimes unpredictable. the tuning process with a (un)supervised learning algorithm does not produce necessarily better results. An online toolkit was developed for this scenario highlighting critical areas in training data, which may pose a challenge for the learning algorithm: irregular data, exceptions in trends, unusual property values. this overview of problematic data might inspire the linguist to enhance the data (for example by dividing a class into more detailed classes). the kit was tested on English and Hungarian corpora. Results show that the preparation of datasets for NP chunking is accelerated effectively, which result in better F-scores. the toolkit runs on a simple browser and its usage poses no difficulties for non-technical users. the tool combines the abstraction ability of a linguist and the power of a statistical engine. © 2018, Springer international Publishing AG, part of Springer Nature.

关键词： Learning algorithms

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Word Level language Identification in Code-Mixed Data using Word Embedding Methods for Indian languages 7

Word Level Language Identification in Code-Mixed Data using ...

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7th international conference on Computing, Communications and Informatics (ICACCI)

作者： Chaitanya, Inumella Madapakula, Indeevar Gupta, Subham Kumar thara, S. Amrita Vishwa Vidyapeetham Dept Comp Sci & Engn Amritapuri India

ISBN: (纸本)9781538653142

In recent years, social media networking has grown to be a marvel of technology in our way of life. Facebook operates the world's leading web-based social networking system with over 2.19 billion clients(as of the first quarter of 2018). As its popularity increased, more individuals from all age demographics, have been accessing this growing phenomenon. Resultant usage of code-mixed data has become an all too common practice in the context of social media. the aim of our project was to identify different languages in the processing of code-mixed data. A comparison of different word embedding methods like Continuous Bag of Words (CBOW) and Skip-Gram models was used to generate feature vectors. these vectors are given as input to the machine learning algorithms like Support Vector Machine, Logistic Regression, K-Nearest Neighbors, Gauss Naive Bayes, Adaboost, and Random Forest which yielded in good crossvalidation scores. the paper also reveals that Precision, Recall, F-Score, Micro and Macro averaging were used as evaluation measures.

关键词： Code mixed Word2Vec Continuous Bag of Words Skip-Gram feature vectors Support Vector Machine Logistic Regression k-Nearest Neighbors Gauss Naive Bayes Adaboost and Random Forest

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languages of baltic countries in digital age 13th

Languages of baltic countries in digital age

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13th international Baltic conference on Databases and information Systems, DB and IS 2018

作者： Skadiņa, Inguna Raiņa bulv. 19 Riga Latvia Institute of Mathematics and Computer Science UL Riga Latvia Tilde Riga Latvia

ISBN: (纸本)9783319975702

Today, when we are surrounded by intelligent digital devices – computers, tablets and mobile phones, we expect communication with these devices in a natural language. Moreover, such communication needs to be in our native language. We also expect that language technologies will not only assist us in everyday tasks, but also will help to overcome problems caused by language barriers. this keynote will focus on language resources and tools that facilitate use of languages of three Baltic countries – Estonian, Latvian and Lithuanian -in digital means (computers, tablets, mobile phones), allow to minimize language barriers, facilitate social inclusion, and support more natural human-computer interaction, thus making digital services more "human". Current situation, technological challenges and most important achievements in language technologies that help to narrow technological gap, facilitates use of natural language for interaction between computer and human, and minimize threat of digital extinction will be presented. © Springer Nature Switzerland AG 2018.

关键词： Speech processing

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