TY - GEN
T1 - Explaining completions produced by embeddings of knowledge graphs
AU - Ruschel, Andrey
AU - Gusmão, Arthur Colombini
AU - Polleti, Gustavo Padilha
AU - Cozman, Fabio Gagliardi
PY - 2019/1/1
Y1 - 2019/1/1
N2 - © Springer Nature Switzerland AG 2019. Advanced question answering typically employs large-scale knowledge bases such as DBpedia or Freebase, and are often based on mappings from entities to real-valued vectors. These mappings, called embeddings, are accurate but very hard to explain to a human subject. Although interpretability has become a central concern in machine learning, the literature so far has focused on non-relational classifiers (such as deep neural networks); embeddings, however, require a whole range of different approaches. In this paper, we describe a combination of symbolic and quantitative processes that explain, using sequences of predicates, completions generated by embeddings.
AB - © Springer Nature Switzerland AG 2019. Advanced question answering typically employs large-scale knowledge bases such as DBpedia or Freebase, and are often based on mappings from entities to real-valued vectors. These mappings, called embeddings, are accurate but very hard to explain to a human subject. Although interpretability has become a central concern in machine learning, the literature so far has focused on non-relational classifiers (such as deep neural networks); embeddings, however, require a whole range of different approaches. In this paper, we describe a combination of symbolic and quantitative processes that explain, using sequences of predicates, completions generated by embeddings.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85072864553&origin=inward
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U2 - 10.1007/978-3-030-29765-7_27
DO - 10.1007/978-3-030-29765-7_27
M3 - Conference contribution
SN - 9783030297640
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 324
EP - 335
BT - Explaining completions produced by embeddings of knowledge graphs
T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 1 January 2019
ER -