Results 131 to 140 of about 101,562 (188)

Multiscore, a gene ranker powered by artificial intelligence and real-world clinical data, shows high sensitivity for the molecular diagnosis of Mendelian disorders in nearly 10,000 exomes and genomes. [PDF]

open access: yesHum Genet
Ustach VD   +17 more
europepmc   +1 more source

Sentiment analysis using cosine similarity measure

2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS), 2015
The opinion of other people is often a major factor influencing our decisions. For a consumer it affects purchase decisions and for a producer or a service provider it helps in making business decisions. Companies spend a lot of money and time on surveys for gathering the public opinion on products and services.
Saprativa Bhattacharjee   +4 more
openaire   +1 more source

Intuitionistic Fuzzy Ordered Weighted Cosine Similarity Measure

Group Decision and Negotiation, 2013
The aim of this paper is to introduce the intuitionistic fuzzy ordered weighted cosine similarity (IFOWCS) measure by using the cosine similarity measure of intuitionistic fuzzy sets and the generalized ordered weighted averaging (GOWA) operator. Some desirable properties and different families of the IFOWCS measure are investigated.
Ligang Zhou   +3 more
openaire   +1 more source

Hierarchical document clustering based on cosine similarity measure

2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), 2017
Clustering is one of the prime topics in data mining. Clustering partitions the data and classifies the data into meaningful subgroups. Document clustering is a set of the document into groups such that two groups show different characteristics with respect to likeness.
Shraddha K. Popat   +2 more
openaire   +1 more source

Fuzzy Lattice Neurocomputing Using Weighted Cosine Similarity Measure

2007 International Joint Conference on Neural Networks, 2007
In this work, we investigate the effects of changing the underlying inclusion measure used by fuzzy lattice neurocomputing (FLN) classifiers to the cosine similarity measures. We also show that by weighing the contribution of each attribute found in the data set, we can provide additional improvements over simply using an inclusion/similarity measure ...
null Al Cripps, Nghiep Nguyen
openaire   +1 more source

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