Recently, large amounts of historical texts have been digitized and made accessible to the
public. Thanks to this, for the first time, it became possible to analyze evolution of language …

Temporal information retrieval has been a topic of great interest in recent years. Its purpose
is to improve the effectiveness of information retrieval methods by exploiting temporal …

As the amount of generated information grows, reading and summarizing texts of large
collections turns into a challenging task. Many documents do not come with descriptive terms, …

In this paper, we present YAKE!, a novel feature-based system for multi-lingual keyword
extraction from single documents, which supports texts of different sizes, domains or languages. …

Optical character recognition (OCR) is one of the most popular techniques used for converting
printed documents into machine-readable ones. While OCR engines can do well with …

Many binary class datasets in real-life applications are affected by class imbalance problem.
Data complexities like noise examples, class overlap and small disjuncts problems are …

The task of Question Answering (QA) has attracted significant research interest for a long
time. Its relevance to language understanding and knowledge retrieval tasks, along with the …

Semantic change—how the meanings of words change over time—has preoccupied scholars
since well before modern linguistics emerged in the late 19th and early 20th century, …

In this work, we propose a lightweight approach for keyword extraction and ranking based on
an unsupervised methodology to select the most important keywords of a single document. …

Social bookmarking is an emerging type of a Web service that helps users share, classify,
and discover interesting resources. In this paper, we explore the concept of an enhanced …