Hits 1.601 – 1.620 of 1.620
1601 |
Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies
|
|
|
|
In: http://research.ijcaonline.org/volume96/number25/pxc3897048.pdf
|
|
BASE
|
|
Show details
|
|
1602 |
©ARC Page 29 Holistic Prediction of Student Attrition in Higher Learning Institutions in Malaysia Using Support Vector Machine Model
|
|
|
|
In: http://www.arcjournals.org/pdfs/ijrscse/v1-i1/4.pdf
|
|
BASE
|
|
Show details
|
|
1603 |
Towards Improvements On Domain-Independent Measurements For Collaborative Assessment
|
|
|
|
In: http://educationaldatamining.org/EDM2011/wp-content/uploads/proc/edm2011_poster2_Anaya.pdf
|
|
BASE
|
|
Show details
|
|
1604 |
2011b. Social Context Summarization
|
|
|
|
In: http://keg.cs.tsinghua.edu.cn/jietang/publications/SIGIR11-Yang-et-al-social-context-summarization.pdf
|
|
BASE
|
|
Show details
|
|
1605 |
Performance Analysis of Learning Classifiers for Spoken Digit Under Noisy Conditions
|
|
|
|
In: http://www.cisjournal.org/journalofcomputing/archive/vol4no3/vol4no3_6.pdf
|
|
BASE
|
|
Show details
|
|
1606 |
Relational Concept Discovery in Structured
|
|
|
|
In: http://www.iro.umontreal.ca/~valtchev/Papiers/valtchev-et-al-DAM-JIM03.pdf.gz
|
|
BASE
|
|
Show details
|
|
1607 |
[Extended Abstract] Why Philosophy? Why Now? Engineering Responds to the Crisis of a Creative Era
|
|
|
|
In: http://philsci-archive.pitt.edu/4513/1/Why-phil-why-now.pdf
|
|
BASE
|
|
Show details
|
|
1608 |
In Search of Cinderella: A Transaction Log Analysis of Folktale Searchers
|
|
|
|
In: http://www.dongnguyen.nl/publications/trieschnigg-enrich2013.pdf
|
|
BASE
|
|
Show details
|
|
1609 |
Web Service Programming for Biological Text Mining
|
|
|
|
In: http://lair.indiana.edu/sigirbio/final/ghanem.pdf
|
|
BASE
|
|
Show details
|
|
1610 |
A Less Cumulative Algorithm of Mining Linguistic Browsing Patterns in the World Wide Web
|
|
|
|
In: http://www.eusflat.org/publications/proceedings/EUSFLAT_2007/papers/Dyczkowski_Krzysztof_(86).pdf
|
|
BASE
|
|
Show details
|
|
1611 |
A Hybrid System Using PSO and Data Mining for Determining the Ranking of a New Participant in
|
|
|
|
In: http://www.cs.bham.ac.uk/~wbl/biblio/gecco2008/docs/p1713.pdf
|
|
BASE
|
|
Show details
|
|
1612 |
Mining Entity Translations from Comparable Corpora: A Holistic Graph Mapping Approach
|
|
|
|
In: http://www.postech.ac.kr/~swhwang/CIKM11a.pdf
|
|
BASE
|
|
Show details
|
|
1613 |
FUZZY MINER: EXTRACTING FUZZY RULES FROM NUMERICAL PATTERNS *
|
|
|
|
In: http://isl.cs.unipi.gr/db/pubs/journals/ijdwm05.pdf
|
|
BASE
|
|
Show details
|
|
1614 |
Learning multiple non-redundant codebooks with word clustering for document classification
|
|
|
|
BASE
|
|
Show details
|
|
1615 |
Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.
|
|
|
|
Abstract:
The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between professional language and consumer friendly language. To keep up with the constantly evolving medical knowledge and language use, new terms need to be identified and added to the OAC CHV. User-generated content on social media, including social question and answer (social Q&A) sites, afford us an enormous opportunity in mining consumer health terms. Existing methods of identifying new consumer terms from text typically use ad-hoc lexical syntactic patterns and human review. Our study extends an existing method by extracting n-grams from a social Q&A textual corpus and representing them with a rich set of contextual and syntactic features. Using K-means clustering, our method, simiTerm, was able to identify terms that are both contextually and syntactically similar to the existing OAC CHV terms. We tested our method on social Q&A corpora on two disease domains: diabetes and cancer. Our method outperformed three baseline ranking methods. A post-hoc qualitative evaluation by human experts further validated that our method can effectively identify meaningful new consumer terms on social Q&A. ; Consumer health information, Consumer health vocabulary, Controlled vocabularies, Ontology enrichment, Social Q&A ; UL1 TR001427 ; This NIH-funded author manuscript originally appeared in PubMed Central at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5488691.
|
|
Keyword:
Consumer Health Information; Controlled; Data Mining; Humans; Internet; Social Media; Translating; Vocabulary
|
|
URL: http://purl.flvc.org/fsu/fd/FSU_pmch_28359728 http://diginole.lib.fsu.edu/islandora/object/fsu%3A640898/datastream/TN/view/Enriching%20consumer%20health%20vocabulary%20through%20mining%20a%20social%20Q%26A%20site.jpg https://doi.org/10.1016/j.jbi.2017.03.016
|
|
BASE
|
|
Hide details
|
|
1617 |
Using data mining to differentiate instruction in college algebra
|
|
|
|
BASE
|
|
Show details
|
|
1618 |
Multi-level mining and visualization of scientific text collections
|
|
|
|
BASE
|
|
Show details
|
|
1620 |
Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study
|
|
|
|
BASE
|
|
Show details
|
|
|
|