Index Link

  • RootNode

Item

{"_buckets": {"deposit": "149fc2d5-0a90-452c-9e1b-830f1c7498cc"}, "_deposit": {"created_by": 73, "id": "7787", "owner": "73", "owners": [73], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "7787"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00007787", "sets": ["user-miit"]}, "communities": ["miit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Tweets  Sentiment  Analysis  for  Healthcare on  Big  Data  Processing  and  IoT  Architecture Using  Maximum  Entropy  Classifier", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "People are too rare to discuss or talk about their health problems with each other and, it is very poor to notice about their realistic health situation. But nowadays, most of the people friendly used social media and people have started expressing their feelings and activities on it. Focus only on Twitter, users’ created tweets composed of news, politics, life conversation which can also be applied for doing a variety of analysis purposes. Therefore, healthcare system is developed to mine about the health state of Twitter user and to provide health authorities to easily check about their continental health behavior based on the Twitter data. Maximum Entropy classifier (MaxEnt) is used to perform senti- ment analysis on their tweets to suggest their health condition (good, fair, or bad). It is interacting with Twitter data (big data environment) and so, Internet of Things (IoT) based big data processing framework is built to be efficiently handled large amount of Twitter user’ data. The aim of this paper is to propose healthcare system using MaxEnt classifier and Big Data processing using Hadoop framework integrated with Internet of Things architecture."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Sentiment analysis, Big data framework, IoT"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2021-01-26"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Published Full Paper.pdf", "filesize": [{"value": "1.5 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_3", "mimetype": "application/pdf", "size": 1500000.0, "url": {"url": "https://meral.edu.mm/record/7787/files/Published Full Paper.pdf"}, "version_id": "cdd1e6f0-9158-4257-b73a-cc69d7c673b3"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICBDL", "subitem_c_date": "May 14-15, 2018", "subitem_conference_title": "Proc. of 1st Intl. Conf.  on Big Data Analysis and Deep Learning (ICBDL), Springer, Japan", "subitem_place": "Japan", "subitem_website": "https://link.springer.com/chapter/10.1007/978-981-13-0869-7_4"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Hein  Htet"}, {"subitem_authors_fullname": "Soe  Soe  Khaing"}, {"subitem_authors_fullname": "Yi  Yi  Myint"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2018-05-06"}, "item_title": "Tweets  Sentiment  Analysis  for  Healthcare on  Big  Data  Processing  and  IoT  Architecture Using  Maximum  Entropy  Classifier", "item_type_id": "21", "owner": "73", "path": ["1582963674932", "1597396989070"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000007787", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2018-05-06"}, "publish_date": "2018-05-06", "publish_status": "0", "recid": "7787", "relation": {}, "relation_version_is_last": true, "title": ["Tweets  Sentiment  Analysis  for  Healthcare on  Big  Data  Processing  and  IoT  Architecture Using  Maximum  Entropy  Classifier"], "weko_shared_id": -1}

Tweets Sentiment Analysis for Healthcare on Big Data Processing and IoT Architecture Using Maximum Entropy Classifier

http://hdl.handle.net/20.500.12678/0000007787
56d9e792-ba43-4b93-8f63-94339dc81e5c
149fc2d5-0a90-452c-9e1b-830f1c7498cc
None
Name / File License Actions
Published Published Full Paper.pdf (1.5 MB)
Publication type
Conference paper
Upload type
Publication
Title
Title Tweets Sentiment Analysis for Healthcare on Big Data Processing and IoT Architecture Using Maximum Entropy Classifier
Language en
Publication date 2018-05-06
Authors
Hein Htet
Soe Soe Khaing
Yi Yi Myint
Description
People are too rare to discuss or talk about their health problems with each other and, it is very poor to notice about their realistic health situation. But nowadays, most of the people friendly used social media and people have started expressing their feelings and activities on it. Focus only on Twitter, users’ created tweets composed of news, politics, life conversation which can also be applied for doing a variety of analysis purposes. Therefore, healthcare system is developed to mine about the health state of Twitter user and to provide health authorities to easily check about their continental health behavior based on the Twitter data. Maximum Entropy classifier (MaxEnt) is used to perform senti- ment analysis on their tweets to suggest their health condition (good, fair, or bad). It is interacting with Twitter data (big data environment) and so, Internet of Things (IoT) based big data processing framework is built to be efficiently handled large amount of Twitter user’ data. The aim of this paper is to propose healthcare system using MaxEnt classifier and Big Data processing using Hadoop framework integrated with Internet of Things architecture.
Keywords
Sentiment analysis, Big data framework, IoT
Conference papers
ICBDL
May 14-15, 2018
Proc. of 1st Intl. Conf. on Big Data Analysis and Deep Learning (ICBDL), Springer, Japan
Japan
https://link.springer.com/chapter/10.1007/978-981-13-0869-7_4
0
0
views
downloads
Views Downloads

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats