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User Localization Based on Call Detail Records
However, one of the main issues in using CDR data is that it is difficult to identify the precise location of the user due to the low spacial resolution of the data and other artifacts such as the load sharing effect.
Legal Document Retrieval using Document Vector Embeddings and Deep Learning
The ensemble model built in this study, shows a significantly higher accuracy level, which indeed proves the need for incorporation of domain specific semantic similarity measures into the information retrieval process.
Semi-Supervised Instance Population of an Ontology using Word Vector Embeddings
With the use of word embeddings in the field of natural language processing, it became a popular topic due to its ability to cope up with semantic sensitivity.
Deriving a Representative Vector for Ontology Classes with Instance Word Vector Embeddings
Selecting a representative vector for a set of vectors is a very common requirement in many algorithmic tasks.
Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similarity
Semantic similarity measures are an important part in Natural Language Processing tasks.
