Predicting market movements based on the sentiment of news media has a long tradition in data analysis.
Disturbances in the job market such as advances in science and technology, crisis and increased competition have triggered a surge in reskilling and upskilling programs.
Inscriptis provides a library, command line client and Web service for converting HTML to plain text.
Most of the current solutions are also built for the more general case of content extraction from web pages and lack key features important for understanding forum content such as the identification of author metadata and information on the thread structure.
Sentic computing relies on well-defined affective models of different complexity - polarity to distinguish positive and negative sentiment, for example, or more nuanced models to capture expressions of human emotions.
This corpus is used to evaluate a series of Named Entity Linking tools in order to understand the impact of the differences in annotation styles on the reported accuracy when processing highly ambiguous entities such as names of creative works.
Performing company valuations within the domain of biotechnology, pharmacy and medical technology is a challenging task, especially when considering the unique set of risks biotech start-ups face when entering new markets.
Gold standard corpora and competitive evaluations play a key role in benchmarking named entity linking (NEL) performance and driving the development of more sophisticated NEL systems.
This paper presents a German corpus for Named Entity Linking (NEL) and Knowledge Base Population (KBP) tasks.
We describe the goals and structure of the game, the underlying application framework, the sentiment lexicons gathered through crowdsourcing, as well as a novel approach to automatically extend the lexicons by means of a bootstrapping process.