About: Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning Goto Sponge NotDistinct Permalink

An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

scholarly article by Prerna Chikersal et al published 2015 in Lecture Notes in Computer Science

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) article scientifique publié en 2015 (fr) наукова стаття, опублікована у 2015 (uk) scholarly article by Prerna Chikersal et al published 2015 in Lecture Notes in Computer Science (en)
publication date	wds:Q57555807-65E12A00-CE3C-47C1-B197-90BE24AE82FA
publication date	2015-01-01 00:00:00Z (xsd:dateTime)
language of work or name	wds:Q57555807-C0422D04-DF8A-4D42-A22F-57AAB9A5DA48
language of work or name	English
author name string	wds:Q57555807-200F6874-C6EB-4FCA-9583-471E861E560F wds:Q57555807-4FAF155C-2B3B-4213-8B51-34FE96203F5D wds:Q57555807-D7826868-09D9-41C3-918B-D4B24C0099D1
author name string	Soujanya Poria Chng Eng Siong Prerna Chikersal
rdfs:label	Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (en) Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (nl)
skos:prefLabel	Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (en) Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (nl)
name	Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (en) Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (nl)
author	wds:Q57555807-2A520154-8544-4274-BD49-E7CE47196527 wds:Q57555807-645AA417-ED63-4DB9-8963-DFE9B3439150
author	Alexander Gelbukh Erik Cambria
title	wds:Q57555807-C2E82E82-BC18-485D-BE2B-7B793C48790B
title	Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning (en)
page(s)	wds:Q57555807-04061077-F931-4A0D-A3AF-B1C0F5B63519
page(s)	49-65
instance of	wds:Q57555807-03DFE62A-8EC7-4D74-9D1B-C1050D4D8DA9
instance of	scholarly article
main subject	wds:Q57555807-A15C905A-3BE7-42E6-9C36-7F7B1756AD3C wds:Q57555807-F171685D-2D7E-44A9-A858-9FA5276EA7BA
main subject	X supervised learning
DBLP publication ID	wds:Q57555807-4E18F67D-C8AC-4EF1-8030-EBB807211A11
DBLP publication ID	https://dblp.org/rec/conf/cicling/ChikersalPCGS15
DBLP publication ID	conf/cicling/ChikersalPCGS15
published in	wds:Q57555807-E814E5FA-4271-4206-9095-3D8DA8A40492
published in	Lecture Notes in Computer Science
DOI	wds:Q57555807-3A6D9247-9A68-48F5-B690-F37CE3739D2B
DOI	http://dx.doi.org/10.1007/978-3-319-18117-2_4
DOI	10.1007/978-3-319-18117-2_4
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q57555807
is cites work of	SenticNet Intra-document and Inter-document Redundancy in Multi-document Summarization Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis Sentic Applications Sentic Patterns Author Profiling with Doc2vec Neural Network-Based Document Embeddings Analysis of Negation Cues for Semantic Orientation Classification of Reviews in Spanish Characteristics of Most Frequent Spanish Verb-Noun Combinations Conclusion Introduction
is cites work of	wds:Q57727682-54BCFC7D-B328-4DD8-B977-4942415D81FD wds:Q57555751-4ED4C83B-BC06-4063-AE9A-41AE689D1F53 wds:Q57727675-50084A77-0D74-4FE2-AAE5-9E7EE4CFBCEA wds:Q57727680-C49FB488-5DD4-4C5D-92B6-57D122F38D3D wds:Q57555727-69038CE9-3732-4CC6-A1F4-19B6C595389C wds:Q57555794-5B37EAD4-B486-40FC-BA4E-1AAC45D50231 wds:Q57555735-D7B6E583-449D-4C18-A19E-0942FC6757E8 wds:Q57727624-FA86BF11-CAFE-4E3A-8CCC-C8044A50677F wds:Q57727650-83657662-995F-4559-9FA7-182A36D6A323 wds:Q57727663-FBFB87C4-0AAD-43FE-9D6B-60AC1E8E4081

Faceted Search & Find service v1.16.117 as of May 05 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3239 as of May 5 2024, on Linux (x86_64-centos_6-linux-gnu), Single-Server Edition (378 GB total memory, 196 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software