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Found 7 papers, 0 papers with code
Multiple Models for Recommending Temporal Aspects of Entities
Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e. g., popularity) is the most important factor in previous work.
How to Search the Internet Archive Without Indexing It
Significant parts of cultural heritage are produced on the web during the last decades.
Balancing Novelty and Salience: Adaptive Learning to Rank Entities for Timeline Summarization of High-impact Events
In this work, we present a novel approach for timeline summarization of high-impact events, which uses entities instead of sentences for summarizing the event at each individual point in time.
Why is it Difficult to Detect Sudden and Unexpected Epidemic Outbreaks in Twitter?
Many studies have shown that this also holds for the medical domain, where Twitter is considered a viable tool for public health officials to sift through relevant information for the early detection, management, and control of epidemic outbreaks.
Learning Dynamic Classes of Events using Stacked Multilayer Perceptron Networks
In general, event-related information needs can be observed in query streams through various temporal patterns of user search behavior, e. g., spiky peaks for popular events, and periodicities for repetitive events.
A Burstiness-aware Approach for Document Dating
A large number of mainstream applications, like temporal search, event detection, and trend identification, assume knowledge of the timestamp of every document in a given textual collection.
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Document Dating
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