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Textual case-based reasoning

2005 Knowledge engineering review (Print)  
This commentary provides a definition of textual case-based reasoning (TCBR) and surveys research contributions according to four research questions.  ...  We also describe how TCBR can be distinguished from text mining and information retrieval. We conclude with potential directions for TCBR research.  ...  Textual case-based reasoning (TCBR) is a subfield of CBR concerned with research and implementation on case-based reasoners where some or all of the knowledge sources are available in textual format.  ... 
doi:10.1017/s0269888906000713 fatcat:ylclz6sbd5fdrp6zoo6adwkdpi

An interactive and user-centered computer system to predict physician's disease judgments in discharge summaries

Jonathan P. DeShazo, Anne M. Turner
2010 Journal of Biomedical Informatics  
Discussion: The results of this study indicate that an interactive training method, de novo knowledge base with no external data sources, and simplified text mining processes can achieve a comparably high  ...  Text classification is performed by interactive, fully supervised learning using rule-based processes and support vector machines (SVMs).  ...  First, the system knowledge base is de novo, that is all of the textual evidence indicating features, negation, and referents arise from within the text without using any external sources of data.  ... 
doi:10.1016/j.jbi.2009.08.016 pmid:19733259 pmcid:PMC2839072 fatcat:qayt7kjptfhrbigpxbfxs63xrq

Programming Language Agnostic Mining of Code and Language Pairs with Sequence Labeling Based Question Answering [article]

Changran Hu, Akshara Reddi Methukupalli, Yutong Zhou, Chen Wu, Yubo Chen
2022 arXiv   pre-print
In this paper, we propose a Sequence Labeling based Question Answering (SLQA) method to mine NL-PL pairs in a PL-agnostic manner.  ...  Fortunately, a Stack Overflow answer post is essentially a sequence of text and code blocks and its global textual context can provide PL-agnostic supplementary information.  ...  In contrast, our Lang2Code pairs are mined with the global textual context of the whole answer post.  ... 
arXiv:2203.10744v1 fatcat:6nrtwkovirclhfvf3grcwjm6iu

Joint Representations of Knowledge Graphs and Textual Information via Reference Sentences

Zizheng JI, Zhengchao LEI, Tingting SHEN, Jing ZHANG
2020 IEICE transactions on information and systems  
The proposed framework consists of knowledge graph representation learning module, textual relation representation learning module, and textual entity representation learning module.  ...  The joint representations of knowledge graph have become an important approach to improve the quality of knowledge graph, which is beneficial to machine learning, data mining, and artificial intelligence  ...  of knowledge graph with the representation learning process of textual information.  ... 
doi:10.1587/transinf.2019edp7229 fatcat:wyzem5xnazg53a6x2mzjcpvx6a

Web Based Pattern Mining and Matching Approach to Question Answering

Dell Zhang, Wee Sun Lee
2002 Text Retrieval Conference  
We describe herein a Web based pattern mining and matching approach to question answering.  ...  Given a new unseen question, these textual patterns can be utilized to extract and rank the plausible answers on the Web.  ...  The power of textual patterns for question answering looks quite amazing and stimulating to us. We describe herein a Web based pattern mining and matching approach to question answering.  ... 
dblp:conf/trec/ZhangL02 fatcat:jv2vllfotbbrdanlskidnfqpwi

Semantic culturomics

Fabian M. Suchanek, Nicoleta Preda
2014 Proceedings of the VLDB Endowment  
If their knowledge is combined with the news articles, it can breathe life into what is otherwise just a sequence of words for a machine.  ...  We predict that this could open up a new field of research, "Semantic Culturomics", in which no longer human text helps machines build up knowledge bases, but knowledge bases help humans understand their  ...  CHALLENGES Mining text in combination with knowledge bases is no easy endeavor. The key challenges would be as follows: Modeling hybrid data.  ... 
doi:10.14778/2732977.2732994 fatcat:c2jvs6jl4rarzaptaqyi4iu4da

Mining history with Le Monde

Thomas Huet, Joanna Biega, Fabian M. Suchanek
2013 Proceedings of the 2013 workshop on Automated knowledge base construction - AKBC '13  
The last decade has seen the rise of large knowledge bases, such as YAGO, DBpedia, Freebase, or NELL.  ...  In this paper, we show how this structured knowledge can help understand and mine trends in unstructured data.  ...  We would like to thank Le Monde for providing us generously with their archive.  ... 
doi:10.1145/2509558.2509567 dblp:conf/cikm/HuetBS13 fatcat:fztwxvshibdt5glwhicnd4ozya

Development and Evaluation of an Intelligence and Learning System in Jurisprudence Text Mining in the Field of Competition Defense

Edna Dias Canedo, Valério Aymoré Martins, Vanessa Coelho Ribeiro, Vinicius Eloy dos Reis, Lucas Alexandre Carvalho Chaves, Rogério Machado Gravina, Felipe Alberto Moreira Dias, Fábio Lúcio Lopes de Mendonça, Ana Lucila Sandoval Orozco, Remis Balaniuk, Rafael T. de Sousa
2021 Applied Sciences  
This paper presents a proposed solution architecture for the jurisprudence search system of the Brazilian Administrative Council for Economic Defense (CADE), with a view to building and expanding the knowledge  ...  techniques to form a supplementary knowledge base, text mining, and machine learning.  ...  with a thesaurus based on standard legal terms and with retrieval based on similar terms.  ... 
doi:10.3390/app112311365 fatcat:btuxpi65bng5fnzmyyto7zo3c4

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,  ...  statistical techniques, natural language processing (NLP), NLP-based morphological analysis, network analysis, and bibliometric to support idea generation.  ...  Similarly, [53] indicated that out-of-domain knowledge, where they referred to it as distant analogies, stimulates idea generation.  ... 
arXiv:2202.12826v1 fatcat:euin4qlcvjfnbbpznw2xbi5cnm

A Classification Model for Mining Research Publications from Crowdsourced Data

Olatunji Mumini Omisore
2015 Bulletin of IEEE Technical Committee on Digital Libraries  
The prospective innovation is to improvise a rich and novel mining approach base on semantic relationship of research documents.  ...  The abstracts look more at modeling textual entailment recognition to determine the semantic relationship in pool of crowdsourced documents on probabilistic setting.  ...  EXPECTED CONTRIBUTIONS This abstract describes the explorations of several textual mining concepts from a purely data-driven perspective, though it is believed that deeper linguistic knowledge can further  ... 
dblp:journals/tcdl/Omisore15 fatcat:n4hz2xxk3vd2fmotxfpgoevlma

An integrated framework for spatio-temporal-textual search and mining

Bingsheng Wang, Haili Dong, Arnold P. Boedihardjo, Chang-Tien Lu, Harland Yu, Ing-Ray Chen, Jing Dai
2012 Proceedings of the 20th International Conference on Advances in Geographic Information Systems - SIGSPATIAL '12  
This paper presents an integrated framework for Spatio-Temporal-Textual (STT) information retrieval and knowledge discovery system.  ...  Specifically, we design an effective prediction prototype with a third-order linear regression model, and present an innovative STT topic modeling relevance ranker to score documents based on inherent  ...  Finally, the ST results are joined with the textual results. STT Ranker STT scores for ranking are computed based on different scoring schemes.  ... 
doi:10.1145/2424321.2424418 dblp:conf/gis/WangDBLYCD12 fatcat:gk73s3ec55cg3dhmt2veoyd4be

iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability [article]

Aman Chadha, Vinija Jain
2021 arXiv   pre-print
Recently, several models have been proposed that have tackled the task of mining causal data from either the visual or textual modality.  ...  By blending causal relationships with the input features to an existing model that performs visual cognition tasks (such as scene understanding, video captioning, video question-answering, etc.), better  ...  These approaches either mine textual snippets such as captions, text blurbs or large-scale knowledge bases such as Wikipedia.  ... 
arXiv:2107.10300v1 fatcat:pgvieshkp5hidmpu6pc25uuwia

Text Mining for Big Data Analysis in Financial Sector: A Literature Review

Mirjana Pejić Bach, Živko Krstić, Sanja Seljan, Lejla Turulja
2019 Sustainability  
(ii) Which techniques are used in the financial sector for textual mining, especially in the era of the Internet, big data, and social media?  ...  Recent research and practice indicate that such information can be interesting for the decision-making process.  ...  Acknowledgments: Authors would like to acknowledge the support and advice provided by the special issue editor, as well as reviewers, which greatly improved the quality of the paper with their comments  ... 
doi:10.3390/su11051277 fatcat:cjkvyvephrf67c4donpui5o5w4

Using multimodal mining to drive clinical guidelines development

Emilie Pasche, Julien Gobeill, Douglas Teodoro, Dina Vishnyakova, Arnaud Gaudinat, Patrick Ruch, Christian Lovis
2011 Studies in Health Technology and Informatics  
These results suggest that combining literature-based discovery with structured data mining can significantly improve effectiveness of decision-support systems for authors of clinical practice guidelines  ...  Compared to our baseline recommendation system based on a question-answering engine built on top of PubMed, an improvement of +16% is observed when clinical data (i.e. resistance profiles) are injected  ...  Column Engine indicates the search model used. Column Multimodal is the type of additional knowledge injected in the model.  ... 
pmid:21893795 fatcat:vv7n2sllanbnrklx2xnkxn2tnu

Discovering business intelligence from online product reviews: A rule-induction framework

Wingyan Chung, Tzu-Liang (Bill) Tseng
2012 Expert systems with applications  
The results indicate that the system achieved high accuracy and coverage related to rule quality, and produced interesting and informative rules with high support and confidence values.  ...  To address these challenges, we propose the development of a new class of BI systems based on rough set theory, inductive rule learning, and information retrieval methods.  ...  Two major pieces of information available in each online review are its textual content and the numerical rating, which respectively indicate the aspects of customer concerns and the customer sentiment  ... 
doi:10.1016/j.eswa.2012.02.059 fatcat:h5joczpeonfz3cor7by5a4pgvu
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