2.8k citations
- Max Planck SocietyDE261 papers
- Saarland UniversityDE124 papers
- Technische Universität BerlinDE55 papers
- Centre National de la Recherche ScientifiqueFR41 papers
- Korea UniversityKR41 papers
- Stanford UniversityUS25 papers
- Institut national de recherche en sciences et technologies du numériqueFR24 papers
- ETH ZurichCH21 papers
- Helmholtz Center for Information SecurityDE20 papers
- Technical University of MunichDE20 papers
- Université de LorraineFR17 papers
- University of LuxembourgLU16 papers
36 papers · 1 filter
Replicating Relevance-Ranked Synonym Discovery in a New Language and Domain
Andrew Yates, Michael Unterkalmsteiner
Domain-specific synonyms occur in many specialized search tasks, such as when searching medical documents, legal documents, and software engineering artifacts. We replicate prior w…
Answering Count Questions with Structured Answers from Text
Shrestha Ghosh, Simon Razniewski, Gerhard Weikum
In this work we address the challenging case of answering count queries in web search, such as ``number of songs by John Lennon''. Prior methods merely answer these with a single,…
Answering Count Queries with Explanatory Evidence
Shrestha Ghosh, Simon Razniewski, Gerhard Weikum
A challenging case in web search and question answering are count queries, such as \textit{"number of songs by John Lennon"}. Prior methods merely answer these with a single, and s…
Law Smells: Defining and Detecting Problematic Patterns in Legal Drafting
Corinna Coupette, Dirk Hartung, Janis Beckedorf +2
Building on the computer science concept of code smells, we initiate the study of law smells, i.e., patterns in legal texts that pose threats to the comprehensibility and maintaina…
Complex Temporal Question Answering on Knowledge Graphs
Zhen Jia, Soumajit Pramanik, Rishiraj Saha Roy +1
Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with temporal intent are a special class of practical importance, but have not received much atte…
You Get What You Chat: Using Conversations to Personalize Search-based Recommendations
Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum
Prior work on personalized recommendations has focused on exploiting explicit signals from user-specific queries, clicks, likes, and ratings. This paper investigates tapping into a…