• No results found

Knowledge Graph Completion via Complex Tensor Factorization

N/A
N/A
Protected

Academic year: 2020

Share "Knowledge Graph Completion via Complex Tensor Factorization"

Copied!
38
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Figure 1: Left: Scores xso = Re(e⊤s W ¯eo) (top) and xos = Re(e⊤o Wes) (bottom) for theproposed complex-valued decomposition, plotted as a function of W ∈ C, for fixedentity embeddings es = 1−2i, and eo = −3+i
Figure 2: Parts of the training, validation and test sets of the generated experiment withone symmetric and one antisymmetric relation
Figure 3: Average precision (AP) for each factorization rank ranging from 5 to 50 for differ-ent state-of-the-art models on the synthetic task
Figure 4: Average precision (AP) for each factorization rank ranging from 5 to 50 for dif-ferent state-of-the-art models on the Kinships data set (top) and on the UMLSdata set (bottom).
+7

References

Related documents

− data consistency checks shall be performed as described in subclause 4.2.1.3. There are three aspects of NE and NR management which can be distinguished: 1) Management of the

of Alizadeh, Brandt, and Diebold (2002), which employs a driftless Brownian motion process. This one day process is replicated for T = 10 , 000 times in order to calculate

Once data is stored in the Cloud, the provider has access to that data and also controls access to that data by other entities (including other users of the Cloud and other

More importantly, it was concluded that corporate governance measures of board gender diversity and board chairman shares ownership and ethics jointly and significantly

interviewing a leadership alumni using a script of 10 questions. They record the interview and then include one-minute video in their electronic newsletter. According to the ED,

For example, the modeling of VMT and Vehicle Hours Traveled (VHT) is done in coordination with four separate modules: along with the AADVMT model in the Travel Demand module

Descriptive research provides information about conditions, situations, and events that occur in the present (Neville,2005). Qualitative approach is selected and chosen by

There are several approaches to train and test the accuracy of the model in supervised learning algorithms. The data set is divided into three groups: training, validation and test