activity
20172019
most citedOn Type-Aware Entity Retrieval

14 citations · 27 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CL2019

Semi-supervised Learning for Word Sense Disambiguation

Darío Garigliotti

This work is a study of the impact of multiple aspects in a classic unsupervised word sense disambiguation algorithm. We identify relevant factors in a decision rule algorithm, inc…

cs.IR2019

Unsupervised Context Retrieval for Long-tail Entities

Darío Garigliotti, Dyaa Albakour, Miguel Martinez +1

Monitoring entities in media streams often relies on rich entity representations, like structured information available in a knowledge base (KB). For long-tail entities, such monit…

cs.IR20191 cited

NeuType: A Simple and Effective Neural Network Approach for Predicting Missing Entity Type Information in Knowledge Bases

Jon Arne Bø Hovda, Darío Garigliotti, Krisztian Balog

Knowledge bases store information about the semantic types of entities, which can be utilized in a range of information access tasks. This information, however, is often incomplete…

cs.IR2018

IntentsKB: A Knowledge Base of Entity-Oriented Search Intents

Darío Garigliotti, Krisztian Balog

We address the problem of constructing a knowledge base of entity-oriented search intents. Search intents are defined on the level of entity types, each comprising of a high-level…

cs.IR2018

Towards an Understanding of Entity-Oriented Search Intents

Darío Garigliotti, Krisztian Balog

Entity-oriented search deals with a wide variety of information needs, from displaying direct answers to interacting with services. In this work, we aim to understand what are prom…

cs.IR2018

Generating High-Quality Query Suggestion Candidates for Task-Based Search

Heng Ding, Shuo Zhang, Darío Garigliotti +1

We address the task of generating query suggestions for task-based search. The current state of the art relies heavily on suggestions provided by a major search engine. In this pap…