[PDF] Top 20 Compositional Vector Space Models for Knowledge Base Completion
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Compositional Vector Space Models for Knowledge Base Completion
... We use the publicly available entity links to Free- base in the ClueWeb dataset (Orr et al., 2013). Hence, we create nodes only for Freebase enti- ties in our KB graph. We remove facts containing /type/object/type ... See full document
11
Improving Neural Knowledge Base Completion with Cross Lingual Projections
... of knowledge, as shown by complementary work from Faruqui et ...Internal models for KB completion, however, make no use of cross-lingual links between entities, which are readily available in ... See full document
7
Traversing Knowledge Graphs in Vector Space
... for models trained with single-edge training: they struggle to answer path queries even when all edges in the path query have been seen at training ...time. Compositional training dramatically reduces these ... See full document
10
Knowledge Base Completion via Coupled Path Ranking
... Feature computation. Once path features are selected, the next step is to compute their values. Given an entity pair (h, t) and a path π, PRA com- putes the feature value as a random walk proba- bility p(t|h, π), i.e., ... See full document
11
LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion
... in knowledge base com- pletion, knowledge base embedding (Bordes et ...which knowledge base completion is formulated as learning a distributed representation (Hinton, ... See full document
8
Representing Text for Joint Embedding of Text and Knowledge Bases
... of knowledge base and textual in- formation was first shown to outperform either source alone in the framework of path-ranking al- gorithms in a combined knowledge base and text graph (Lao et ... See full document
11
Random Walks and Neural Network Language Models on Knowledge Bases
... 300-dimensional space, and have been shown to out- perform other distributional corpus-based methods on several tasks, including the WS353 word similar- ity dataset (Baroni et ... See full document
6
Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text
... the knowledge base embedding approach has gained a signifi- cant amount of attention, due to its simple predic- tion time computation and strong empirical perfor- mance (Nickel et ...edge base are ... See full document
11
An Open-World Extension to Knowledge Graph Completion Models
... KGC models with pre-trained word em- ...embedding space to graph-based embedding space, where we can now apply the graph-based model for predicting ...prediction models from which we can pick ... See full document
8
Feature Rich Networks for Knowledge Base Completion
... feature models that jointly embed the KB symbols and text relations into the same space (Riedel et ...such models over relation extraction systems is that they can combine both the internal structure ... See full document
6
Neighborhood Mixture Model for Knowledge Base Completion
... ized by averaging the pre-trained word vectors (Mikolov et al., 2013; Pennington et al., 2014). It is not surprising as many entity names in Word- Net and FreeBase are lexically meaningful. It is possible for all other ... See full document
11
Reasoning Over Paths via Knowledge Base Completion
... based knowledge base completion (KBC) ...our knowledge this is the first paper that is fo- cused on trying to use path ranking to identify relevant entities bridging a pair of known entities ... See full document
8
Compositional Matrix Space Models for Sentiment Analysis
... model compositional effects for senti- ment at the phrase- and ...hand-code compositional rules in or- der to model compositional effects of combining dif- ferent words in the ...domain ... See full document
11
Augmentic Compositional Models for Knowledge Base Completion Using Gradient Representations
... numerous models of graph data deployed in knowledge base com- pletion (KBC), in which embeddings of entities and relations are combined into composite repre- sentations—pairs of entities in a ... See full document
10
The Role of Syntax in Vector Space Models of Compositional Semantics
... such vector spaces. A gen- eral framework for semantic vector composition was proposed in Mitchell and Lapata (2008), with Mitchell and Lapata (2010) and more recently Bla- coe and Lapata (2012) providing ... See full document
11
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... present vector space semantic parsing (VSSP), a general framework for building compositional models of vector space ...produce vector space ... See full document
10
Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction
... look for paths connecting the two nodes, the fea- ture space is equivalent to PRA’s, and this is the same as running PRA and binarizing the resultant feature vectors. However, because we do not have to compute ... See full document
11
Entity Disambiguation by Knowledge and Text Jointly Embedding
... BoW representations have several intrinsic drawbacks: First, the semantic meaning of a di- mension is largely ignored. For example, “cat”, “cats” and “tree” are equally distant under one- hot BoW representations. Second, ... See full document
10
Type Sensitive Knowledge Base Inference Without Explicit Type Supervision
... encode the type(s) of entity e, where, by ‘type’, we loosely mean “information that helps decide if e can participate in a relation r, as subject or object.” Heuristic filtering of the entities that do not match the ... See full document
6
“Not not bad” is not “bad”: A distributional account of negation
... distributional models, and the integration of distributional el- ements in logical ...matrix-vector models similar to that of Socher et ...such models, and thus show that negation cannot ... See full document
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