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Found 6 papers, 0 papers with code
Klout Topics for Modeling Interests and Expertise of Users Across Social Networks
This paper presents Klout Topics, a lightweight ontology to describe social media users' topics of interest and expertise.
Analyzing users' sentiment towards popular consumer industries and brands on Twitter
In this paper, we analyze the opinion of 19M Twitter users towards 62 popular industries, encompassing 12, 898 enterprise and consumer brands, as well as associated subject matter topics, via sentiment analysis of 330M tweets over a period spanning a month.
Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media
In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction from noisy user generated text on social media.
High-Throughput and Language-Agnostic Entity Disambiguation and Linking on User Generated Data
The Entity Disambiguation and Linking (EDL) task matches entity mentions in text to a unique Knowledge Base (KB) identifier such as a Wikipedia or Freebase id.
DAWT: Densely Annotated Wikipedia Texts across multiple languages
In addition to the main dataset, we open up several derived datasets including mention entity co-occurrence counts and entity embeddings, as well as mappings between Freebase ids and Wikidata item ids.
Modeling context and situations in pervasive computing environments
In pervasive computing environments, various entities often have to cooperate and integrate seamlessly in a \emph{situation} which can, thus, be considered as an amalgamation of the context of several entities interacting and coordinating with each other, and often performing one or more activities.
