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A COVID-19 Search Engine (CO-SE) with Transformer-based Architecture [article]

Shaina Raza
2022 arXiv   pre-print
This problem motivates us to propose the design of the COVID-19 Search Engine (CO-SE), which is an algorithmic system that finds relevant documents for each query (asked by a user) and answers complex  ...  questions by searching a large corpus of publications.  ...  To facilitate natural language searches, CO-SE employs machine learning and deep neural network-based techniques.  ... 
arXiv:2206.03474v1 fatcat:gyqvy3tl7bbfhgvhk7kknmqiou

Ontology research and development. Part 1 - a review of ontology generation

Ying Ding, Schubert Foo
2002 Journal of information science  
Through this survey, we have identified that shallow information extraction and natural language processing techniques are deployed to extract concepts or classes from free-text or semi-structured data  ...  However, relation extraction is a very complex and difficult issue to resolve and it has turned out to be the main impediment to ontology learning and applicability.  ...  They combine the techniques from information retrieval, machine learning and artificial intelligence for concept and rule learning.  ... 
doi:10.1177/016555150202800204 fatcat:4m54xekncrcgtjqrxnhnngpib4

Ontology research and development. Part 1: A review of ontology generation

Y. Ding, S. Foo
2002 Journal of Information Science  
Through this survey, we have identified that shallow information extraction and natural language processing techniques are deployed to extract concepts or classes from free-text or semi-structured data  ...  However, relation extraction is a very complex and difficult issue to resolve and it has turned out to be the main impediment to ontology learning and applicability.  ...  They combine the techniques from information retrieval, machine learning and artificial intelligence for concept and rule learning.  ... 
doi:10.1177/0165551024234020 fatcat:rmhtay6t75d2vm2xbpu3wbiixe

A SOFTWARE INFRASTRUCTURE FOR RESEARCH IN TEXTUAL DATA MINING

LARS E. HOLZMAN, TODD A. FISHER, LEON M. GALITSKY, APRIL KONTOSTATHIS, WILLIAM M. POTTENGER
2004 International journal on artificial intelligence tools  
A unique capability of TMI is support for optimization. This facilitates text mining research by automating the search for optimal parameters in text mining algorithms.  ...  We also discuss how the TMI utilizes existing machine-learning libraries, thereby enabling researchers to continue and extend their endeavors with minimal effort.  ...  The authors would also like to thank the following co-workers for their contributions to this work: Jirada Kuntraruk  ... 
doi:10.1142/s0218213004001843 fatcat:plygoomlzvbrreg3dku63bboze

Multilayer Music Representation and Processing: Key Advances and Emerging Trends

Federico Avanzini, Luca A. Ludovico
2019 2019 International Workshop on Multilayer Music Representation and Processing (MMRP)  
This work represents the introduction to the proceedings of the 1 st International Workshop on Multilayer Music Representation and Processing (MMRP19) authored by the Program Co-Chairs.  ...  The authors explored a technique for symbolic melody generation, constrained by a given chord progression.  ...  Well structured formats, in turn, need efficient and accurate techniques that allow to automate content production for such formats, by analyzing and synchronizing information across various representation  ... 
doi:10.1109/mmrp.2019.8665370 fatcat:tta7xe2oivhdnczoi7xae4cf6a

Industry–Academia Research Collaboration and Knowledge Co-creation: Patterns and Anti-patterns

Dusica Marijan, Sagar Sen
2022 ACM Transactions on Software Engineering and Methodology  
This article reports on the experience of research collaboration and knowledge co-creation between industry and academia in software engineering as a way to bridge the research–practice collaboration gap  ...  Increasing the impact of software engineering research in the software industry and the society at large has long been a concern of high priority for the software engineering community.  ...  For instance, signal processing experts use techniques for transforming signals in a time domain to a frequency domain, to obtain different features for reasoning about sensor data, while machine learning  ... 
doi:10.1145/3494519 fatcat:b5capq3ybncapddvn5rnec5ayu

Report on INEX 2009

T. Beckers, S. Geva, W.-C. Huang, T. Iofciu, J. Kamps, G. Kazai, M. Koolen, S. Kutty, M. Landoni, M. Lehtonen, V. Moriceau, P. Bellot (+17 others)
2010 SIGIR Forum  
XML-Mining Track Investigating structured document mining, especially the classification and clustering of semi-structured documents.  ...  INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results  ...  The second main research question was the impact of more verbose queries-using either the XML structure, or using multi-word phrases.  ... 
doi:10.1145/1842890.1842897 fatcat:46evgkszirdm3grr6fqrtuyqtm

HDDI™: Hierarchical Distributed Dynamic Indexing [chapter]

William M. Pottenger, Yong-Bin Kim, Daryl D. Meling
2001 Data Mining for Scientific and Engineering Applications  
Despite significant accomplishments in internetworking, however, scalable indexing and data-mining techniques for computational knowledge management lag behind the rapid growth of distributed collections  ...  A novel approach to information clustering based on the contextual transitivity of similarity between terms is introduced.  ...  We also gratefully acknowledge the assistance of the many who worked together with us at the National Center for Supercomputing Applications and at Lehigh University to make this a reality.  ... 
doi:10.1007/978-1-4615-1733-7_18 fatcat:jc4omkimvrgvroatlbeyg35eyu

Combining Unsupervised, Supervised, and Rule-based Algorithms for Text Mining of Electronic Health Records - A Clinical Decision Support System for Identifying and Classifying Allergies of Concern for Anesthesia During Surgery

Geir Thore Berge, Ole-Christoffer Granmo, Tor Oddbjørn Tveit
2017 Information Systems Development  
Our approach is novel in that it utilizes unsupervised machine learning to analyze large corpora of narratives to automatically build a clinical language model containing words and phrases of which meanings  ...  The system incorporates unsupervised and supervised machine learning algorithms in combination with rule-based algorithms to identify and classify allergies of concern for anesthesia during surgery.  ...  Figure 1 shows the overall CDSS architecture, which combines EHR data extraction techniques, pre-processing techniques, unsupervised and supervised machine learning techniques with rule-based techniques  ... 
dblp:conf/isdevel/BergeGT17 fatcat:duj5k42y7vc4xoqgn4byn2k7de

A Survey of Automatic Extraction of Personal Name Alias from the Web

A. Muthusamy, A. Subramani
2014 International Journal of Signal Processing, Image Processing and Pattern Recognition  
In future, we need to model a lexico syntactical pattern for extracting the alias from snippets then word co-occurrence for measuring the association between words.  ...  It also describes about how the aliases are ranked, then page counts on the web, word co-occurrence using anchor text and techniques like term frequency (tf), inverse document frequency (idf), log likelihood  ...  Subramani and the management of K.S.R Educational Institutions for the valuable guidance and support.  ... 
doi:10.14257/ijsip.2014.7.6.07 fatcat:danh3vub2vg7jcffoxkdm4dygu

Towards extracting supporting information about predicted protein-protein interactions [article]

Adam Roth, Sandeep Subramanian, Madhavi Ganapathiraju
2015 bioRxiv   pre-print
We describe UPSITE, a text mining tool for extracting evidence in support of a hypothesized interaction.  ...  We suggest that presenting annotations of the two proteins in a PPI side-by-side and a score that quantifies their similarity lessens this burden to some extent.  ...  The computational and statistical mechanisms of supervised learning algorithms are well understood by machine learning specialists, but wet-lab researchers often have difficulty accepting output as valid  ... 
doi:10.1101/031591 fatcat:azxblwzvijcwjph2yhcgav26ee

Integrating data and text mining processes for digital library applications

Robert Sanderson, Paul Watry
2007 Proceedings of the 2007 conference on Digital libraries - JCDL '07  
This paper explores the integration of text mining and data mining techniques, digital library systems, and computational and data grid technologies with the objective of developing an online classification  ...  workflows; the outcomes of a demonstrator based on the National Library of Medicine's Medline dataset; and the provision of comparable metrics for evaluation purposes.  ...  There are several key techniques which have been integrated into Cheshire3: part of speech tagging, phrase chunking, and deep parsing of the grammatical structures.  ... 
doi:10.1145/1255175.1255188 dblp:conf/jcdl/SandersonW07 fatcat:6idcrh5khvbr3geskbeou2ycau

The state of the art in ontology learning: a framework for comparison

MEHRNOUSH SHAMSFARD, AHMAD ABDOLLAHZADEH BARFOROUSH
2003 Knowledge engineering review (Print)  
This paper presents the state of the art in Ontology Learning (OL) and introduces a framework for classifying and comparing OL systems.  ...  OL system for their own domain or application.  ...  (XML, DTD) and structured (DB schema, ontology) data German, XML, HTML, DTD Resource processing + shallow text processing by SMES Association rules + formal concept analysis + clustering  ... 
doi:10.1017/s0269888903000687 fatcat:fpwvgzgs75ccvhp72e3g3eqe3a

Automated subject classification of textual web documents

Koraljka Golub
2006 Journal of Documentation  
Purpose -To provide an integrated perspective to similarities and differences between approaches to automated classification in different research communities (machine learning, information retrieval and  ...  science, as well as for practitioners.  ...  There are other examples of applying machine--learning techniques to web pages and categorizing them into browsable structures. Mladenic (1998) and Labrou and Finin (1999) used the Yahoo!  ... 
doi:10.1108/00220410610666501 fatcat:cdlhrejd7jfmzlxn7q646xk3ya

Coupled semi-supervised learning for information extraction

Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka, Tom M. Mitchell
2010 Proceedings of the third ACM international conference on Web search and data mining - WSDM '10  
This paper pursues the thesis that much greater accuracy can be achieved by further constraining the learning task, by coupling the semi-supervised training of many extractors for different categories  ...  Semi-supervised training using only a few labeled examples is typically unreliable because the learning task is underconstrained.  ...  We also gratefully acknowledge Jamie Callan for making available his collection of web pages, Yahoo! for use of their M45 computing cluster, and the anonymous reviewers for their comments.  ... 
doi:10.1145/1718487.1718501 dblp:conf/wsdm/CarlsonBWHM10 fatcat:wiecoon73bbffkjvkzlxqbn2ky
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