[PDF] Top 20 Entity/Event Level Sentiment Detection and Inference
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Entity/Event Level Sentiment Detection and Inference
... Sentiment Corpus. Annotated corpora of reviews (e.g., (Hu and Liu, 2004; Titov and McDonald, 2008)), widely used in NLP, often include target an- notations. Such targets are often aspects or features of products ... See full document
9
Robust Entity Clustering via Phylogenetic Inference
... each entity mention arises from copying and option- ally mutating an earlier name from a sim- ilar ...posterior inference and an empirical evalu- ation on several ... See full document
11
Using Cross Entity Inference to Improve Event Extraction
... Our event extraction system adopts a step-by- step cross-entity inference to predict ...candidate event mention and tag its event type based on consistency of entity ...of ... See full document
10
JEDI: Joint Entity and Relation Detection using Type Inference
... an entity prunes the number of potential relations that this entity can partici- pate ...other entity and one of the pair’s members due to in- ferred type ... See full document
6
Document level Sentiment Inference with Social, Faction, and Discourse Context
... plicit sentiment, while preserving consistency. The sentiment dynamics in social groups, moti- vated by social science theories, are encoded as soft ILP ...one entity is likely to agree with the ... See full document
11
Multi-entity Sentiment Scoring
... of sentiment in differing degrees have been ...A sentiment composition model is described which uses a cascade of transducers relying on lexical sentiment seeds, a phrasal chunker, and hand-written ... See full document
6
Joint Inference for Event Coreference Resolution
... Within-document event coreference resolution is the task of determining which event mentions in a text refer to the same real-world ...event. Event coreference is arguably more challenging and ... See full document
12
Revisiting Joint Modeling of Cross document Entity and Event Coreference Resolution
... interdependent entity and event cluster- ing, incrementally constructing the final clustering ...the entity and event clus- tering processes. When predicting event clusters, the ... See full document
11
Using Document Level Cross Event Inference to Improve Event Extraction
... an entity participates in different types of events in a single ...Attack event, and recorded the roles they were assigned for other event ...other event-role combinations appeared in total ... See full document
9
Joint Prediction for Entity/Event Level Sentiment Analysis using Probabilistic Soft Logic Models
... Previously, we (Deng et al., 2013; Deng and Wiebe, 2014; Deng et al., 2014) develop rules and models to infer sentiments related to +/-effect events, events that positively or negatively affect entities. That work ... See full document
11
MPQA 3 0: An Entity/Event Level Sentiment Corpus
... One issue is whether an attitude toward an entity or event is indeed communicated in the sentence. Con- sider this sentence: “President Mugabe’s reelection has been praised by OAU.” The OAU is positive to- ... See full document
6
Social Web Observatory: An entity driven, holistic information summarization platform across sources
... pipeline, entity detection and aspect-based and document-level sentiment analysis (Petasis et ...contain entity mentions are kept for further ...all sentiment of each textual ... See full document
9
Ruchi: Rating Individual Food Items in Restaurant Reviews
... 1150 sentiment sentences hand selected from restaurant reviews that included food names, and sentiments of each of these sentences were manually ...Our sentiment evaluation results obtained for differ- ent ... See full document
6
Real-time service quality monitoring through mining sparse Twitter data
... sengers’ sentiment information as another class of observations, is utilized to face the chal- lenge of scarce ...burstiness. Sentiment information brings external knowledge into the prob- lem of ... See full document
33
International Journal of Computer Science and Mobile Computing
... The baseline (BL) in our experiments is using the total review with unigrams (Uni), bigrams (Bi), and their combination (Uni?Bi) as features. We split each review into twoequal halves and carry out experiments using the ... See full document
9
Text mining brain imaging reports
... disease entity in either the report or conclusions part of the ...stroke entity which is in a location relation (mod:loc) with a cortical loca- tion entity (loc:cortical) and in a time relation ... See full document
11
Overview of the Infectious Diseases (ID) task of BioNLP Shared Task 2011
... in event annota- tion (TO) leading annotator training and annotation scheme ...final entity annotation to be no lower than 90% F-score and that of the event annotation to be no lower than 75% F-score ... See full document
10
Large-scale news entity sentiment analysis
... a sentiment word is present in this window (see the discussion in Section ...negative sentiment values in that word window help identify the polarity re- garding the mentioned ...2,300 sentiment ... See full document
9
Identifying Event Sentiment Association using Lexical Equivalence and Co reference Approaches
... The theory maintains that consecutive discourse elements, termed text spans, are related by a rela- tively small set (20–25) of rhetorical relations. But, instead of identifying the rhetorical relations, the present task ... See full document
9
Joint Inference for Event Timeline Construction
... Research in temporal reasoning recently received much attention. Allen (1983) introduced an interval based temporal logic which has been used widely in the field. Recent efforts in building an annotated temporal corpus ... See full document
11
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