Search Results for author:
Found 9 papers, 5 papers with code
SemTUI: a Framework for the Interactive Semantic Enrichment of Tabular Data
The large availability of datasets fosters the use of \acrshort{ml} and \acrshort{ai} technologies to gather insights, study trends, and predict unseen behaviours out of the world of data.
On the Impact of Temporal Representations on Metaphor Detection
To the best of our knowledge, this is the first study that examines the metaphor detection task with a detailed exploratory analysis where different temporal and static word embeddings are used to account for different representations of literal meanings.
SWEAT: Scoring Polarization of Topics across Different Corpora
Understanding differences of viewpoints across corpora is a fundamental task for computational social sciences.
Tough Tables: Carefully Evaluating Entity Linking for Tabular Data
Table annotation is a key task to improve querying the Web and support the Knowledge Graph population from legacy sources (tables).
Knowledge Graph Embeddings and Explainable AI
Knowledge graph embeddings are now a widely adopted approach to knowledge representation in which entities and relationships are embedded in vector spaces.
Compass-aligned Distributional Embeddings for Studying Semantic Differences across Corpora
In this paper, we present a general framework to support cross-corpora language studies with word embeddings, where embeddings generated from different corpora can be compared to find correspondences and differences in meaning across the corpora.
Training Temporal Word Embeddings with a Compass
Temporal word embeddings have been proposed to support the analysis of word meaning shifts during time and to study the evolution of languages.
TWINE: A real-time system for TWeet analysis via INformation Extraction
In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams.
