Argument mining is a core technology for automating argument search in large document
collections. Despite its usefulness for this task, most current approaches to argument mining …

Considering the widespread use of mobile and voice search, answer passage retrieval for
non-factoid questions plays a critical role in modern information retrieval systems. Despite …

With the rise in mobile and voice search, answer passage retrieval acts as a critical
component of an effective information retrieval system for open domain question answering …

In this work we address the problem of argument search. The purpose of argument search is
the distillation of pro and contra arguments for requested topics from large text corpora. In …

Concept maps can be used to concisely represent important information and bring structure
into large document collections. Therefore, we study a variant of multi-document …

There exists an ever-growing set of data-centric systems that allow data scientists of varying
skill levels to interactively manipulate, analyze and explore large structured data sets …

Efficiently exploring a collection of text documents in order to answer a complex question is
a challenge that many people face. As abundant information on almost any topic is …

Relevance feedback techniques assume that users provide relevance judgments for the top
k (usually 10) documents and then re-rank using a new query model based on those …

Automatic summarization has so far focused on datasets of ten to twenty rather short
documents, typically news articles. But automatic systems could in theory analyze hundreds …

We release HindiRC dataset, a new publicly available Reading Comprehension dataset for
grade based comprehension. Popular works on reading comprehension don't make a …