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Using Machine Learning and Text Mining in Question Answering [chapter]

Antonio Juárez-González, Alberto Téllez-Valero, Claudia Denicia-Carral, Manuel Montes-y-Gómez, Luis Villaseñor-Pineda
2007 Lecture Notes in Computer Science  
It applies machine learning and text mining techniques to identify the most probable answers to factoid and definition questions respectively.  ...  Experimental results on the Spanish Question Answering task at CLEF 2006 show that the proposed architecture can be a practical solution for monolingual question answering by reaching a precision as high  ...  The answer extraction for factoid questions is based on a machine learning method.  ... 
doi:10.1007/978-3-540-74999-8_49 fatcat:6evuboxhfbdehgqa65ybztdpt4

Automatic Online Subjective Text Evaluation using Text Mining

2019 International journal of recent technology and engineering  
In educational sector Question Answer (QA) evaluation has done using semantic as well as semantic analysis in many approaches.  ...  Numerous existing mechanisms have implemented using different machine learning algorithms.  ...  different information mining (statistical and machine learning) calculations.  ... 
doi:10.35940/ijrte.i8725.078219 fatcat:nz5yp3qmqvhhjffdb2hpu7rzl4

A Review on Automated Disease Diagnosis Techniques

Sunena Rose M V, Dr. Sobhana N. V
2017 IJARCCE  
Using this system health seeker will get immediate response as compared to the existing system. Diseases and symptoms are collected and used as the Question Answer pairs.  ...  In shallow learning methods, which make use of patient details from hospital records with structured fields, they can focus on only a single or a few diseases.  ...  In this method, it first mines the medical signatures from the text data and applied to sparse deep learning network.  ... 
doi:10.17148/ijarcce.2017.63187 fatcat:bxgqlbcyyzc5tjstmb6xdc6ogi

Review on Text Analytics an Approach to Artificial Intelligence

Vaishnavi D. Fate
2019 International Journal for Research in Applied Science and Engineering Technology  
Text analytics supports organizations in managing unstructured information, identifying connections and relationships in information, and in extracting relevant entities to improve knowledge management  ...  Extracting meaning out of this text is an incredibly complicated task since texts may have different contexts and formats.  ...  Machine learning for natural language processing and text analytics involves using machine learning algorithms and "narrow" artificial intelligence (AI) to understand the meaning of text documents.  ... 
doi:10.22214/ijraset.2019.6251 fatcat:g2d3rot64zasvgmka5kfpinyua

Autonomous Educational Testing System Using Unsupervised Feature Learning

Anwaya Aras, Shree Ranjani, Jannat Talwar, Mangesh Bedekar
2013 International Journal on Integrating Technology in Education  
Although a substantial amount of work has been done in the field of e-learning, specifically in automation of objective question and answer evaluation, personalized learning, adaptive evaluation systems  ...  In addition the process of manually correcting students' answers is a cumbersome and tedious task especially where the class size is large.  ...  The goal of text categorisation in this context is categorising the question according to the topic chosen.Using machine learning the objective is to learn classifiers from examples which do the categorisation  ... 
doi:10.5121/ijite.2013.2304 fatcat:zwpgarfrmrhxffo465robw2xq4

An Analysis of the Applications of Natural Language Processing in Various Sectors [chapter]

Priya B, Nandhini J.M, Gnanasekaran T
2021 Advances in Parallel Computing  
It involves creating algorithms that transform text in to words labeling With the emerging advancements in Machine learning and Deep Learning, NLP can contributed a lot towards health sector, education  ...  , agriculture and so on.  ...  Machine Learning and NLP Machine Learning algorithms and Artificial Intelligence are used in Machine learning for NLP and text analytics to identify and understand the meaning of text documents.  ... 
doi:10.3233/apc210109 fatcat:bt77hv4rwrdh7kttj6l43vdchu

Report on KDD conference 2004 panel discussion can natural language processing help text mining?

Anne Kao, Steve Poteet
2004 SIGKDD Explorations  
Historically, Data Mining researchers have come out of the statistics, database and machine learning communities.  ...  With large amounts of text data now available on-line, both on the Internet and in corporate repositories, text mining is an area of growing interest.  ...  ACKNOWLEDGMENTS We wish to thank all the panelists for their participation, as well as the help and encouragement from our team in the Boeing Phantom Works, Mathematics and Computing Technology.  ... 
doi:10.1145/1046456.1046478 fatcat:ckuals2dyfhh3etwd2bpa5uwju

A Survey on Question –Answering System

Anjali Saini, P.K. Yadav
2017 International Journal Of Engineering And Computer Science  
A Question -Answering system consists of three core components i.e. question classification ,information retrieval and answer extraction module.  ...  Question-Answering(QA) is a new research area/ region in the field of Information science which comes into focus in last few decade.  ...  Text Mining also referred to as text data mining, roughly equal or identical to text analytics, which refers to the process of finding high quality information from text.  ... 
doi:10.18535/ijecs/v6i3.09 fatcat:bxn5625qavbhdpbmixjxbqzaw4

An Optimization Mining Algorithm for Analyzing Students' Learning Degree Based on Dynamic Data

Zengzhen Shao, Hongxu Sun, Xiao Wang, Zhongzhi Sun
2020 IEEE Access  
The traditional static data only analyzes the students' learning degree based on the students' final answer, but ignores the dynamic data in the process of answering questions, such as the modification  ...  The algorithm first uses the optimized text classification technology to match the question texts to the knowledge points automatically, so as to improves the efficiency and quality.  ...  ACKNOWLEDGMENT The authors are grateful to the anonymous reviewers for their constructive comments and invaluable contributions to enhance the presentation of this article.  ... 
doi:10.1109/access.2020.3001749 fatcat:eoc3el4ainacjg42pfybqdayzq

call for papers - International Conference on Data Mining and NLP (DNLP 2020)

PETER
2020 Zenodo  
based Methods  Text Mining  NLP and Machine Learning  NLP and Computational Linguistics  NLP and Information Retrieval  NLP and AI, Data Mining Paper Submission Authors are invited to submit papers  ...   Parsing/Grammatical Formalisms  Phonology, Morphology  POS Tagging  Question Answering  Semantic Processing  Speech Recognition and Synthesis  Spoken Language Processing  Statistical and Knowledge  ...  /Shallow Parsing Speech Recognition and Synthesis  Spoken Language Processing  Statistical and Knowledge based Methods  Text Mining  NLP and Machine Learning  NLP and Computational Linguistics  NLP  ... 
doi:10.5281/zenodo.4013157 fatcat:wa4gyjf4xvhhvf4nudbqxwmswi

Classification of Proactive Personality: Text Mining Based on Weibo Text and Short-answer Questions Text

Peng Wang, Yun Yan, Yingdong Si, Gancheng Zhu, Xiangping Zhan, Jun Wang, Runsheng Pan
2020 IEEE Access  
With participants' Weibo text and short-answer questions text, we proposed a new approach to classify individuals' proactive personality based on text mining technology.  ...  In order to make classification, five machine learning algorithms included Support Vector Machine (SVM), XGBoost, K-Nearest-Neighbors (KNN), Naive Bayes (NB) and Logistic Regression (LR) were deployed.  ...  Machine learning algorithms such as BP neural networks [34] and Bayesian theory [32] [35] were widely used in the process of text classification tasks.  ... 
doi:10.1109/access.2020.2995905 fatcat:uqd4sd5hkncmthkoplb63yrrfa

International Conference on Data Mining and NLP (DNLP 2020)

Rusev
2020 Zenodo  
based Methods  Text Mining  NLP and Machine Learning  NLP and Computational Linguistics  NLP and Information Retrieval  NLP and AI, Data Mining Paper Submission Authors are invited to submit papers  ...   Parsing/Grammatical Formalisms  Phonology, Morphology  POS Tagging  Question Answering  Semantic Processing  Speech Recognition and Synthesis  Spoken Language Processing  Statistical and Knowledge  ...  /Shallow Parsing Speech Recognition and Synthesis  Spoken Language Processing  Statistical and Knowledge based Methods  Text Mining  NLP and Machine Learning  NLP and Computational Linguistics  NLP  ... 
doi:10.5281/zenodo.4047733 fatcat:ra6lrlysh5gqrazxr3lfredtxi

A Systematic Literature Review about Idea Mining: The Use of Machine-driven Analytics to Generate Ideas [article]

Workneh Y. Ayele, Gustaf Juell-Skielse
2022 arXiv   pre-print
The results of this study indicate that idea generation through machine-driven analytics applies text mining, information retrieval (IR), artificial intelligence (AI), deep learning, machine learning,  ...  The results include a list of techniques and procedures in idea generation through machine-driven idea analytics. Additionally, characterization and heuristics used in idea generation are summarized.  ...  For example, in computer science, text mining combines data mining, knowledge management, IR, NLP, and machine learning [20] .  ... 
arXiv:2202.12826v1 fatcat:euin4qlcvjfnbbpznw2xbi5cnm

A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques [article]

Mehdi Allahyari, Seyedamin Pouriyeh, Mehdi Assefi, Saied Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys Kochut
2017 arXiv   pre-print
Additionally, we briefly explain text mining in biomedical and health care domains.  ...  In this paper, we describe several of the most fundamental text mining tasks and techniques including text pre-processing, classification and clustering.  ...  Thus, text mining techniques along with statistical machine learning algorithms are widely used in biomedical domain.  ... 
arXiv:1707.02919v2 fatcat:uiwsrz6wgrb65dcnp54wmkrase

Analysis of English Multitext Reading Comprehension Model Based on Deep Belief Neural Network

Qiaohui Tang, Syed Hassan Ahmed
2021 Computational Intelligence and Neuroscience  
Secondly, the text reader is designed, and the deep belief neural network is introduced to predict the question answering probability.  ...  In order to solve the problems of low accuracy and low efficiency of answer prediction in machine reading comprehension, a multitext English reading comprehension model based on the deep belief neural  ...  Finally, BLEU-4 and ROUGE-L evaluation methods are used to analyse the machine learning performance of text readers in real data ets, and the final results are shown in Figure 9 .  ... 
doi:10.1155/2021/5100809 pmid:34567102 pmcid:PMC8457992 fatcat:ry34jyzbnfgxfa7566rxfwc2ze
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