Abstract: The disclosed search engine and search engine system apply a variety of criteria to find specific information within a full-text dataset, even when its user cannot recall the exact text or exact spelling of the desired information. The criteria cause retrieval of text not only when the sequence of words in the query matches the sequence of words in the text identically but also when the difference between sequences is that one of the words in a sequence is missing, added, replaced, or replaced with a synonymous word or a word having phonetic similarity. Another criterion is that the two words in the query sequence differ in order from the two words in the text sequence to be retrieved. The above criteria are applied after stop list words are disregarded. The search engine accordingly enables a user to find text more easily in large full-text datasets by inexact text searching.

Abstract: Useful search results are obtained when the search logic retrieves, not only text strings, or “words,” that match exactly the search arguments but also when the search logic retrieves phonetically similar words, which are misspelled. The method and system disclosed herein provide both results faster than known conventional methods and systems, and in some embodiments such speed may be achieved using conventional resources as described.

Abstract: Useful search results are obtained when the search logic retrieves, not only text strings, or “words,” that match exactly the search arguments but also when the search logic retrieves phonetically similar words, which are misspelled. The method and system disclosed herein provide both results faster than known conventional methods and systems, and in some embodiments such speed may be achieved using conventional resources as described.

Abstract: Suspicious activity may be found by automated methods and systems that analyze data records to find association rules correlating values in the fields of the records and then analyzing the association rules, as the association rules themselves can be indicative of improprieties. Thus, minimal human intervention is used to find improprieties in even very large datasets. If the data records are records of sales transactions, the finding and the analyzing of association rules as disclosed can flag suspicious-appearing transactions that may have resulted from improprieties, such as human mistakes or intentional frauds. Instructions for performing the disclosed analyses may be stored on non-transitory storage media for access by systems to execute the automated methods.

Abstract: Suspicious activity may be found by automated methods and systems that analyze data records to find association rules correlating values in the fields of the records and then analyzing the association rules, as the association rules themselves can be indicative of improprieties. Thus, minimal human intervention is used to find improprieties in even very large datasets. If the data records are records of sales transactions, the finding and the analyzing of association rules as disclosed can flag suspicious-appearing transactions that may have resulted from improprieties, such as human mistakes or intentional frauds. Instructions for performing the disclosed analyses may be stored on non-transitory storage media for access by systems to execute the automated methods.

Abstract: A mechanism for ensuring secure e-commerce transactions, which includes the process of writing a limited server that can only perform those actions that are required. This server may optionally be a single function server, enabled to implement one or more commands only. Alternative actions are simply not coded into the program. In this way the server is intentionally limited, in that it is programmed to handle the limited set of commands that are relevant for the specific field in which it operates.

Abstract: A system and method for collaborative filtering of data, such that accurate real time recommendations can be provided to users, without prior rating by users. The invention's main purpose is to discover the purchasing patterns of the users (customers) of a particular vendor (this includes stores or other points of sale, such as service businesses), whether they are virtual places on the Internet or conventional offline places.

Abstract: A method and system for predicting an unknown value of an attribute of interest of a given item from a population of items, each item in the population having a plurality of variable attributes including the attribute of interest. Known attribute values regarding a training sample of items within the population including the attribute of interest are stored in a memory. The stored attribute values are processed to determine association rules regarding the training sample, including at least one generalized association rule, each association rule including one or more conditions on one or more respective attribute values of the items predictive of the value of the attribute of interest, and the at least one generalized rule including a logical combination of a plurality of such conditions using at least one logical operation from the group consisting of disjunction and negation. Data are received from an input device, the data including values of at least some of the attributes of the given item.