AI Software Technologies, Artificial Intelligence Development Technologies

AI Software Technologies, Artificial Intelligence Development Technologies
April 30, 2014

AI Software Technologies, Artificial Intelligence Development Technologies



Optimization Suite

Constraint programming is a programming paradigm wherein relations between variables are stated in the form of constraints. Constraints differ from the common primitives of imperative programming languages in that they do not specify a step or sequence of steps to execute, but rather the properties of a solution to be found. This makes constraint programming a form of declarative programming.

The CP paradigm consists of a set of variables, each of which have a set of possible values (their domain) and a set of constraints between the variables that specify which combinations of values are allowed and which are not.

Brighterion's constraint programming technology is a complete language that integrates the following concepts:

Variables: Real numbers, integers, enumerated, sets, matrices, vectors, intervals, fuzzy subsets and more.
Arithmetic Constraints: : =, +, -, *, /, /=, >, <, ?, ?, interval addition, interval subtraction, interval multiplication, interval division, max, min, intersection, union, exponential, modulo, logarithm and more.
Temporal Constraints: Temporal constraints including equal, nequal, before, after, meets, overlaps, starts, finishes and personal temporal operators such as disjoint, started-by, overlapped-by, met-by, finished-by and more.
Boolean Constraints: Or, and, not, xor, implication, equivalence
Symbolic Constraints: Inclusion, union, intersection, cardinality, belonging and more.
Fuzzy Constraints: To achieve the best possible solution in cases where no exact solution exists.

Brighterion's constraint programming technology relieves programmers of the burden of learning a new language. Most programmers can generate their first optimization program in less than one hour.

Data Mining

Data mining is the process of extracting knowledge from data by uncovering previously unknown useful information and relationships.

iPrevent's Data Mining algorithms (over a dozen different algorithms) also include the following tools:
Data Quality: error correction, outlier detection, imputation of missing values, feature selection, incoherence correction, data preparation & enrichment algorithms, etc.
Statistics: regression analysis, correlation, multiple comparison, CHAID, etc.
Probabilistic Inference: Bayesian networks, graphical model, hierarchical and probabilistic cluster analysis, etc.
Association rule learning
Graphical Visualization

Text Mining

Text mining is the discovery of previously unknown information by automatically extracting information from unstructured or structured text files.

Brighterion Text Mining:
Automatically identifies entities, relationships (link analysis), topics, categories and clusters.
Goes far beyond screening for vocabulary and uses a proprietary Fuzzy Logic and thesaurus-indexing algorithms that can extract the meaning from documents.
Supports many formats such as: HTML, XML, plain text, PDF, Microsoft Office, etc.
Allows parallel processing of large amounts of data with high throughput.

Velocity Analyzer

iPrevent's Velocity Analyzer enables financial institutions to monitor a wide variety of customer and merchant data, such as production purchasing patterns, suspicious changes in activities, and number of transactions over a period of time. iPrevent Velocity Analyzer uses a powerful compression technique to save transactions for optimal scalability and performance.

Additionally, institutions can monitor:
Payment method history and typical purchasing
Patterns at the merchant's site
E-mail address activity
Ship-to/Bill-to activity
Refund Watch, Manual T-Log
Excessive Cash Back
Decline Analyzer
Excessive Failed Pre-Authorizations
Unattended and Attended Transactions