In the sense-level similarity, the task is to compute the degree of semantic similarity of a pair of concepts. This similarity is high for jewel1n and gem5n which are both referring to the same jewelry object. The third sense of gem, though still related to the jewelry sense, has a ...
Implementation of IROS20 paper - "Semantic Graph Based Place Recognition for 3D Point Clouds" slamautonomous-drivingplace-recognitionlidar-point-cloudsemantic-mappinggraph-neural-networksgraph-similarity UpdatedJul 25, 2024 Python cszhangzhen/H2MN ...
Computer science A graph-based approach for semantic data mining UNIVERSITY OF OREGON Dejing Dou LiuHaishanData mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is widely acknowledged that the role of domain knowledge in the ...
We also provide aSematch-Demo Server. You can use it for experimenting with main functionalities or take it as an example for using Sematch to develop applications. Please check ourDocumentationfor more details. Computing Word Similarity The core module of Sematch is measuring semantic similarity bet...
An interactive graph-based approach for mining omics data on the Semantic WebLysenko, ArtemHindle, Matthew MorrittRawlings, Christopher JohnSplendiani, Andrea
(3)EmbAssi.We use the vector representation for similarity search in graph databases following the filter-verification paradigm, building upon established indices for the Manhattan (ℓ1) distance on vectors. Our approach supports range queries as well ask-nearest neighbor search using the optimal mu...
That is, in a given context, i.e., an object pair, the probabilities of different predicates to describe this pair are related to their semantic similarity. For example, “person-ride-horse” (Fig. 3b) is similar to “person-ride-elephant” (Fig. 3f), since “horse” and “elephant”...
In the field of object detection, due to the complexity of realistic scenarios, the objects are mostly obscured and semantic-confusable. The existing CNNs-
Francis-Landau M, Durrett G, Klein D.Capturing semantic similarity for entity linking with convolutional neural networks[C]Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics. Stroudsburg: Association for Computational Linguistics, 2016: 1256-12...
19. HAP:Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation LearningTKDE 20211. Graph Classification 2. Graph Matching 3. Graph Similarity LearningNoneIMDB-B, IMDB-M, COLLAB, MUTAG, PROTEINS, PTC // synthetic datasets (graph matching) // AIDS, LINUX (graph ...