Abstract: A social media location posting system a payment card transaction authorization processor and a location posting service processor. The payment card transaction authorization processor is configured to receive over a network a payment card transaction authorization request for a cardholder and store in a computer storage file associated with the cardholder payment card transaction data included in the authorization request. The location service processor is configured to post over the network at least a portion the payment card transaction data stored in the file associated with the cardholder to a social media site associated with the cardholder.

Abstract: A natural language parse ranker of a natural language processing (NLP) system employs a goodness function to rank the possible grammatically valid parses of an utterance. The goodness function generates a statistical goodness measure (SGM) for each valid parse The parse ranker orders the parses based upon their SGM values. It presents the parse with the greatest SGM value as the one that most likely represents the intended meaning of the speaker. The goodness function of this parse ranker is highly accurate in representing the intended meaning of a speaker. It also has reasonable training data requirements. With this parse ranker, the SGM of a particular parse is the combination of all of the probabilities of each node within the parse tree of such parse. The probability at a given node is the probability of taking a transition (“grammar rule”) at that point.

Abstract: A system for developing semantic schema for natural language processing has a semantic runtime engine and a semantic authoring tool. The semantic runtime engine is adapted to map a natural language input to a semantic schema and to return the mapped results to an application domain. The semantic authoring tool is adapted to receive user input for defining the semantic schema and to interact with the semantic runtime engine to test the semantic schema against a query.

Abstract: A natural language parse ranker of a natural language processing (NLP) system employs a goodness function to rank the possible grammatically valid parses of an utterance. The goodness function generates a statistical goodness measure (SGM) for each valid parse. The parse ranker orders the parses based upon their SGM values. It presents the parse with the greatest SGM value as the one that most likely represents the intended meaning of the speaker. The goodness function of this parse ranker is highly accurate in representing the intended meaning of a speaker. It also has reasonable training data requirements. With this parse ranker, the SGM of a particular parse is the combination of all of the probabilities of each node within the parse tree of such parse. The probability at a given node is the probability of taking a transition (“grammar rule”) at that point.

Abstract: A method and grammar checking system are provided that generate a stochastic score, or a statistical goodness measure, for each of an input string of text and one or more alternative strings of text. An alternative generator generates the alternative strings of text, and a ranking parser produces parse trees and corresponding statistical goodness measures for each of the strings. The string of text having the highest goodness measure is selected for recommendation to a user.

Abstract: A method of calculating trigram path probabilities for an input string of text containing a multi-word-entry (MWE) or a factoid includes tokenizing the input string to create a plurality of parse leaf units (PLUs). A PosColumn is constructed for each word, MWE, factoid and character in the input string of text which has a unique first (Ft) and last (Lt) token pair. TrigramColumns are constructed which define corresponding TrigramNodes each representing a trigram for three PosColumns. Forward and backward trigram path probabilities are calculated for each separate TrigramNode. The sums of all trigram path probabilities through each PLU are then calculated as a function of the forward and backward trigram path probabilities. Systems and computer-readable medium configured to implement the methods are also provided.

Abstract: A method of, and system for, generating a sentence from a semantic representation maps the semantic representation to an unordered set of syntactic nodes. Simplified generation grammar rules and statistical goodness measure values from a corresponding analysis grammar are then used to create a tree structure to order the syntactic nodes. The sentence is then generated from the tree structure. The generation grammar is a simplified (context free) version of a corresponding full (context sensitive) analysis grammar. In the generation grammar, conditions on each rule are ignored except those directly related to the semantic representation. The statistical goodness measure values, which are calculated through an analysis training phase in which a corpus of example sentences is processed using the full analysis grammar, are used to guide the generation choice to prefer substructures most commonly found in a particular syntactic/semantic context during analysis.