Abstract: Systems and methods are disclosed for monitoring models monitoring Internet-connected devices. Systems and methods include receiving, from an Internet-connected devices monitoring system, training data, the Internet-connected devices monitoring system being configured to predict future maintenance needs and/or failures of at least one Internet-connected device. Systems and methods further include receiving, from the Internet-connected devices monitoring system, production data associated with the at least one Internet-connected device, and determining that a data distance metric between the training data and the production data exceeds a first predetermined risk threshold. Systems and methods further include determining a risk level to be associated with the Internet-connected devices monitoring model based on the determination that the data distance metric exceeds the first predetermined risk threshold.

Abstract: Systems and methods are disclosed for monitoring models monitoring Internet-connected devices. Systems and methods include receiving, from an Internet-connected devices monitoring system, training data, the Internet-connected devices monitoring system being configured to predict future maintenance needs and/or failures of at least one Internet-connected device. Systems and methods further include receiving, from the Internet-connected devices monitoring system, production data associated with the at least one Internet-connected device, and determining that a data distance metric between the training data and the production data exceeds a first predetermined risk threshold. Systems and methods further include determining a risk level to be associated with the Internet-connected devices monitoring model based on the determination that the data distance metric exceeds the first predetermined risk threshold.

Abstract: There is provided a method for searching a database to obtain data. The method includes (a) prioritizing a set of keys that are derived from a match inquiry, thus yielding a prioritized set of keys, wherein the prioritizing is based on, for each key of the set, an efficacy of using the key, (b) determining a subset of the prioritized set, and (c) retrieving, using the subset, a set of candidates for satisfying the match inquiry.

Abstract: A method for generating a relevance score for at least one candidate retrieved in a search, the method comprising: initiating a query seeking at least one the candidate based upon at least one filter selected from the group consisting of: product name, product category, company name, HS code, SIC code and any other product-related qualifier; searching at least one database for matches between the candidate and the filter, thereby generating at least one matched candidate; generating an initial relevance score for each the matched candidate; generating at least one additional score for each the matched candidate, wherein the additional score is at least one selected from the group consisting of: a reputation score, a score boost, a past behavior score, a profile match score, a preference match score and a web behavior score; and generating a final relevance score based upon the initial relevance score and the at least one additional score for each the matched candidate.

Abstract: There is provided a method for searching a database to obtain data. The method includes (a) prioritizing a set of keys that are derived from a match inquiry, thus yielding a prioritized set of keys, wherein the prioritizing is based on, for each key of the set, an efficacy of using the key, (b) determining a subset of the prioritized set, and (c) retrieving, using the subset, a set of candidates for satisfying the match inquiry.

Abstract: A system and method for finding a business entity in a database that matches input data. A web services interface accepts a match request and provides a best match. A pre-processing layer cleans, parses, and standardizes input data into terms. An application layer includes a match engine for processing the match request using the terms. The match engine evaluates and scores match candidates from the database to provide the best match and, optionally, an ordered list of match candidates.

Abstract: Techniques for generating a visual data model include providing first and second objects that represent first and second portions of data from a model; assigning attributes to the first and second objects, the attributes representing characteristics of the first and second portions of the data; providing a relationship object that represents a relationship between the first and second objects; and assigning, to the relationship object, a relationship attribute representing a characteristic of the relationship between the first and second objects.

Abstract: A system and method for finding a business entity in a database that matches input data. A web services interface accepts a match request and provides a best match. A pre-processing layer cleans, parses, and standardizes input data into terms. An application layer includes a match engine for processing the match request using the terms. The match engine evaluates and scores match candidates from the database to provide the best match and, optionally, an ordered list of match candidates.