Entity linking is a standard component in modern retrieval system that is often performed by
third-party toolkits. Despite the plethora of open source options, it is difficult to find a single …

Knowledge Graphs (KG) are of vital importance for multiple applications on the web,
including information retrieval, recommender systems, and metadata annotation …

In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the
context of information retrieval (IR). Modern IR systems can benefit from information …

Entity-oriented search systems often learn vector representations of entities via the
introductory paragraph from the Wikipedia page of the entity. As such representations are …

Pre-trained language models such as BERT have been a key ingredient to achieve state-of-
the-art results on a variety of tasks in natural language processing and, more recently, also …

Entity-oriented search tasks heavily rely on exploiting unstructured and structured
collections. Moreover, it is frequent for text corpora and knowledge bases to provide …

Factoid entity questions (FEQ), which seek answers in the form of a single entity from
knowledge sources such as DBpedia and Wikidata, constitute a substantial portion of user …

With the development of deep learning and natural language processing techniques, pre-
trained language models have been widely used to solve information retrieval (IR) …

ALSC (Aspect-level Sentiment Classification) is a fine-grained task in the field of NLP
(Natural Language Processing) which aims to identify the sentiment toward a given aspect …

Machine understanding of user utterances in conversational systems is of utmost importance
for enabling engaging and meaningful conversations with users. Entity Linking (EL) is one of …