From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

Publications associées (24)

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Graph Chatbot

Interpreting Language Models Through Knowledge Graph Extraction

Martin Jaggi, Vinitra Swamy, Angeliki Romanou

Transformer-based language models trained on large text corpora have enjoyed immense popularity in the natural language processing community and are commonly used as a starting point for downstream tasks. While these models are undeniably useful, it is a c ...

2021

Graph Embeddings for One-pass Processing of Heterogeneous Queries

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong

Effective information retrieval (IR) relies on the ability to comprehensively capture a user's information needs. Traditional IR systems are limited to homogeneous queries that define the information to retrieve by a single modality. Support for heterogene ...

IEEE COMPUTER SOC2020

Quantifying Engagement with Citations on Wikipedia (Part 2)

Robert West, Tiziano Piccardi, Giovanni Colavizza

Wikipedia is one of the most visited sites on the Web and a common source of information for many users. As an encyclopedia, Wikipedia was not conceived as a source of original information, but as a gateway to secondary sources: according to Wikipedia's gu ...

RUSSIAN NATL PUBLIC LIBRARY SCIENCE & TECHNOLOGY2020

Quantifying Engagement with Citations on Wikipedia

Robert West, Tiziano Piccardi, Giovanni Colavizza

ASSOC COMPUTING MACHINERY2020

Approaching Ontology Alignment through Representation Learning to Bridge the Semantic Gap in Engineering Applications

Prodromos Kolyvakis

The current information landscape is characterised by a vast amount of relatively semantically homogeneous, when observed in isolation, data silos that are, however, drastically semantically fragmented when considered as a whole. Within each data silo, inf ...

EPFL2020

Deep Feature Factorization For Content-Based Image Retrieval And Localization

Sabine Süsstrunk, Edo Collins

State of the art content-based image retrieval algorithms owe their excellent performance to the rich semantics encoded in the deep activations of a convolutional neural network. The difference between these algorithms lies mostly in how activations are co ...

IEEE2019

User Guidance for Efficient Fact Checking

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, howev ...

2019

User Guidance for Efficient Fact Checking

Thành Tâm Nguyên, Thanh Trung Huynh, Quoc Viet Hung Nguyen

ASSOC COMPUTING MACHINERY2019

Extracting And Aligning Artist Names in Digitized Art Historical Archives

Frédéric Kaplan, Isabella Di Lenardo, Benoît Laurent Auguste Seguin

The largest collections of art historical images are not found online but are safeguarded by museums and other cultural institutions in photographic libraries. These collections can encompass millions of reproductions of paintings, drawings, engravings and ...

Red de Humanidades Digitales A. C.2018

Mapping Affinities in Academic Organizations

Frédéric Kaplan, Dario Rodighiero, Boris Beaude

Scholarly affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, an ...

2018

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