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Found 4 papers, 1 papers with code
Language Models as Context-sensitive Word Search Engines
Context-sensitive word search engines are writing assistants that support word choice, phrasing, and idiomatic language use by indexing large-scale n-gram collections and implementing a wildcard search.
The Impact of Main Content Extraction on Near-Duplicate Detection
Commercial web search engines employ near-duplicate detection to ensure that users see each relevant result only once, albeit the underlying web crawls typically include (near-)duplicates of many web pages.
Towards Axiomatic Explanations for Neural Ranking Models
We investigate whether one can explain the behavior of neural ranking models in terms of their congruence with well understood principles of document ranking by using established theories from axiomatic IR.
Heuristic Feature Selection for Clickbait Detection
We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017.
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