The fundamental issue with opinion mining is to select the right approach for right problem to solve. The common approaches used for opinion mining are

     > parts of speech

     > n-grams using thesaurus  and

     > text mining

Each of these  approaches is used for a specific problem, for example to know the general mood of a population on some incidence or news/event, or to know sentiment for a market ,stock or company we may use the parts of speech. But we might not use parts of speech for an issue for which the thesaurus is not built yet. When we need to capture and develop thesaurus for that particular issue n-grams approach will be a good fit. For some other problems we might need to perform text mining, like clustering and classification.  The bottom-line is no single approach solves all problems.

We have 13 years of Research and Development experience in Microarray Gene Expression analysis. Finding differential expression for a group of genes is a np-complete problem. Most of the software either work in gene space or in sample space. Very few of the software which work in both spaces either eliminate low signals or apply some statistical threshold - thus eliminating latent biological signals which are very vital in gene expression analysis.

GePIC is the only software in industry which eliminates this problem and is based on its predecessor BTSVQ. GePIC generates sample clusters based on differential expression and generates novel visualizations of highly multidimensional data into 2D.

(predictive) Models are learned from the historical data. This learning is not trivial nor an exact science. The historical data need to be explored to discover the underlying distributions in it. Assuming wrong statistical distribution leads to using wrong parameters and  hence garbage-in-garbage-out.

We master the art of exploratory data analysis and use combination of distributions which truly represent your data and then learn models using state-of-the art as well as our proprietary methods which yield minimum false positives

North American ATM industry is 27 billion dollar annual loss industry, out of this roughly 27% is the loss due to dead cash in the ATM machines overnight (or the replenish period).  intelliCast can save you over 20% in the dead cash using our proven forecasting techniques. intelliCast is can be accessed in the cloud or deployed as an appliance at your premises. The appliance is built as per your organization needs and is customized for maximum throughput through parallel processing.

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