AI Medical Compendium Topic:
Semantics

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A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words.

Computational intelligence and neuroscience
With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive an...

Evaluating a pivot-based approach for bilingual lexicon extraction.

Computational intelligence and neuroscience
A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like English. In this paper, in order to show validity and usability of the pivot-based approach, we evalua...

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

Journal of biomedical informatics
BACKGROUND: Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially...

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

PloS one
Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog informati...

Incorporating linguistic knowledge for learning distributed word representations.

PloS one
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashio...

Semantic network mapping of religious material: testing multi-agent computer models of social theories against real-world data.

Cognitive processing
Agent-based modeling allows researchers to investigate theories of complex social phenomena and subsequently use the model to generate new hypotheses that can then be compared to real-world data. However, computer modeling has been underutilized in r...

Encoding sequential information in semantic space models: comparing holographic reduced representation and random permutation.

Computational intelligence and neuroscience
Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random pe...

Learning document semantic representation with hybrid deep belief network.

Computational intelligence and neuroscience
High-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural languag...

Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach.

Journal of biomedical informatics
Identifying unknown drug interactions is of great benefit in the early detection of adverse drug reactions. Despite existence of several resources for drug-drug interaction (DDI) information, the wealth of such information is buried in a body of unst...

Sentiment analysis using common-sense and context information.

Computational intelligence and neuroscience
Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the r...