585 results about "Inference engine" patented technology

A method, system and computer program product for assessing information security interviews users regarding technical and non-technical issues. In an embodiment, users are interviewed based on areas of expertise. In an embodiment, information security assessments are performed on domains within an enterprise, the results of which are rolled-up to perform an information security assessment across the enterprise. The invention optionally includes application specific questions and vulnerabilities and/or industry specific questions and vulnerabilities. The invention optionally permits users to query a repository of expert knowledge. The invention optionally provides users with working aids. The invention optionally permits users to execute third party testing/diagnostic applications. The invention, optionally combines results of executed third party testing/diagnostic applications with user responses to interview questions, to assess information security. A system in accordance with the invention includes an inference engine, which may include a logic based inference engine, a knowledge based inference engine, and/or an artificial intelligence inference engine. In an embodiment, the invention includes an application specific tailoring tool that allows a user to tailor the system to assess security of information handled by a third party application program.

A system and method for providing online insurance quotes to a client on a social network web site includes an insurance server adapted to execute a coverage calculator application and an insurance database in communication with the insurance server for storing a plurality of personas, a plurality of insurance coverage options associated with each persona, and a price quote associated with each insurance coverage option. The system is in communication with a platform application on the social network web site. The platform application is in communication with a social network database for storing user content of the social network client. In one embodiment, the platform application uses an inference engine to query the user content of the social network client and return a set of inferred characteristics. The coverage calculator application selects a persona in response to the set of inferred characteristics and selects one of the insurance coverage options in response to the selected persona.

The current disclosure uses the disciplines of Ontology and Epistemology to implement a context/content-based “multimedia conceptual search and planning”, in which the formation of conceptualization is supported by embedding multimedia sensation and perception into a hybrid database. The disclosed system comprises: 1) A hybrid database model to host concept setup. 2) A graphic user interface to let user freely issue searching request in text and graphic mode. 3) A parsing engine conducting the best match between user query and dictionaries, analyzing queried images, detecting and presenting shape and chroma, extracting features/texture of an object. (4) A translation engine built for search engine and inference engine in text and graphic mode. 5) A search engine using partitioned, parallel, hashed indexes from web crawler result, conducting search in formal/natural language in text and graphic mode. 6) A logic interference engine working in text and graphic mode, and 7) A learning/feedback interface.

Apparatus with accompanying subsystems and methods for developing conversational computer applications. As a user interface, the apparatus allows for a user to initiate the conversation. The apparatus also answers simple and complex questions, understands complex requests, pursues the user for further information when the request is incomplete, and in general provides customer support with a human like conversation while, at the same time, it is capable to interact with a company's proprietary database. As a development tool, the apparatus allows a software developer to implement a conversational system much faster than takes, with current commercial systems to implement basic dialog flows. The apparatus contains three major subsystems: a state transition inference engine, a heuristic answer engine and a parser generator with semantic augmentations. A main process broker controls the flow and the interaction between the different subsystems. The state transition inference engine handles requests that require processing a transaction or retrieving exact information. The heuristic answer engine answers questions that do not require exact answers but enough information to fulfill the user's request. The parser generator processes the user's natural language request, that is, it processes the syntactical structure of the natural language requests and it builds a conceptual structure of the request. After the parser generator processes the user's request, a main process broker feeds the conceptual structure to either the heuristic answer engine or to the state transition inference engine. The interaction between the main process broker and the subsystems creates a conversational environment between the user and the apparatus, while the apparatus uses information from proprietary databases to provide information, or process information, during the course of the conversation. The apparatus is equipped with a programming interface that allows implementers to declare and specify transactions based requests and answers to a multiplicity of questions. The apparatus may be used with a speech recognition interface, in which case, the apparatus improves the recognition results through the context implicitly created by the apparatus.

A virtual assistant learning system is presented. A monitoring device, a cell phone for example, observes user interactions with an environment by acquiring sensor data. The monitoring device uses the sensor data to identify the interactions, which in turn is provided to an inference engine. The inference engine leverages the interaction data and previously stored knowledge elements about the user to determine if the interaction exhibits one or more user preferences. The inference engine can use the preferences and interactions to construct queries targeting search engines to seek out possible future interactions that might be of interest to the user.

This invention involves an electronic catalog system which employs the knowledge and experience of a "Sales Agent", which is provided to a computer data base, and used with an inference engine to assist and guide actual customers to products that they will most likely be interested in purchasing. This system is employs hypothetical questions and answers, based on the sales agents experience with generic customers, as well as criteria and constraints provided by both the Sales Agent and the electronic catalog content.

An information retrieval system that deals with the problems of synonymy, polysemy, and retrieval by concept by allowing for a wide margin of uncertainty in the initial choice of keywords in a query. For each input query vector and an information matrix, the disclosed system solves an optimization problem which maximizes the stability of a solution at a given level of misfit. The disclosed system may include a decomposition of the information matrix in terms of orthogonal basis functions. Each basis encodes groups of conceptually related keywords. The bases are arranged in order of decreasing statistical relevance to a query. The disclosed search engine approximates the input query with a weighted sum of the first few bases. Other commercial applications than the disclosed search engine can also be built on the disclosed techniques.

A gesture-based recognition system obtains a vehicle occupant's desired command inputs through recognition and interpretation of his gestures. An image of the vehicle's interior section is captured and the occupant's image is separated from the background, in the captured image. The separated image is analyzed and a gesture recognition processor interprets the occupant's gesture from the image. A command actuator renders the interpreted desired command to the occupant along with a confirmation message, before actuating the command. When the occupant confirms, the command actuator actuates the interpreted command. Further, an inference engine processor assesses the occupant's state of attentiveness and conveys signals to a drive assist system if the occupant in inattentive. The drive-assist system provides warning signals to the inattentive occupant if any potential threats are identified. Further, a driver recognition module readjusts a set of vehicle's personalization functions to pre-stored settings, on recognizing the driver.

Methods, systems, and computer program products for identifying computer source code constructs are disclosed. According to one method, computer source code is converted to a format suitable for an automated inference engine. The automated inference engine receives as inputs the converted source code, a set of elemental design patterns defining patterns to be identified, and a set of rules defining relationships between patterns. The automated inference engine outputs proofs indicative of patterns present in the source code. The proofs may be converted to a source code pattern report.

Customizable software provides assurances about the ability of an IP network to satisfy security, regulatory and availability requirements by comprehensive vulnerability and compliance assessment of IP networks through automated analysis of configurations of devices such as routers, switches, and firewalls. The solution comprises three main approaches for testing of IP device configurations to eliminate errors that result in vulnerabilities or requirements compliance issues. The first two fall in to the “static constraint validation” category since they do not change significantly for each IP network, while the last approach involves incorporation of each specific IP network's policies/requirements. These approaches are complementary, and may be used together to satisfy all the properties described above. The first approach involves checking the configurations of devices for conformance to Best-Current-Practices provided by vendors (e.g. Cisco Network Security Policy) and organizations such as the NIST, NSA or CERT. Also this includes checks of compliance with regulations such as FISMA, SOX, HIPPA, PCI, etc. The second approach is where as one reads device configurations, one collects beliefs about network administrator intent. As each belief is collected, an inference engine checks whether the new belief is inconsistent with previously accumulated beliefs. The third approach addresses the multiple device/protocol issue by including an understanding of high-level service and security requirements about the specific IP network under test from the network administrators.

A system for inferring intent of visitors to a Website has a visitor-tracking application executing from a digital medium coupled to a server hosting the Website, the server connected to a repository adapted to store data about visitor behavior, and an inference engine for processing the data to infer the intent of visitors. Visitor behavior relative to links is tracked, and intent of a visitor is inferred from one or both, or a combination of analysis of the behavior and deducing meaning for anchor text of links selected.

A system for electronic crime reduction is provided, comprising a computer system, a database, a malware de-compiler, a malware parser, and an inference engine. The database contains information that associates electronic crime attack signature data with at least one of an individual, a group, and a location. The malware de-compiler, when executed on the computer system, translates a first malware executable to an assembly language version. The first malware is associated with an electronic crime that has been committed. The malware parser, when executed on the computer system, analyzes the assembly language version to identify distinctive coding preferences used to develop the first malware. The inference engine, when executed on the computer system, analyzes the distinctive coding preferences identified by the malware parser application in combination with searching the database to identify one of an individual, a group, and a location associated with the electronic crime.

The Cooperative Biometrics Abnormality Detection (C-BAD) system is a network of sensors that track personnel throughout physical locations, communications, and computer systems. These systems are then linked to a central computer that contains detailed information on the individual, and rule-based risk, relationship, and abnormality models that will deter, detect, and document possible insiders. It is only at this point that C-BAD will then objectively report suspicious activities to a supervisory team for further investigation. (C-BAD) This System replaces previous current labor-intensive, subjective analysis, which has proven to be a weak deterrent and fraught with human error. C-BAD uses a full spectrum of sensors that identify personnel through the use of contact, contactless, biometrics, smart cards, or a combination of any one of these. The C-BAD central monitoring computer contains an inference engine based on artificial intelligence or a rule-based system, which reviews databases and furnished information.

A machine learning based automated online form-filling technique provides for automatically completing user input controls based on previously stored information. An associative parser is used to identify and associate characteristics related to form controls with the corresponding form controls. The characteristics of the user input controls are input into a machine learning based semantic inference engine that was trained for the purpose of identifying the type of information that is supposed to be input into various user input controls. The semantic inference engine operates to label the controls in a manner that describes the meaning of the control, i.e., the type of information that should be automatically input into the corresponding controls. Consequently, the user input controls can be automatically filled in with previously stored user profile information associated with the corresponding labels.

A system and method facilitating network diagnostics and self-healing is provided. The invention includes a data stream monitor component adapted to selectively copy protocol specific subset(s) of raw network data and provide the subset(s) of data to a diagnostics engine. The invention further includes a diagnostic engine adapted to facilitate network diagnostics and/or self-healing.

The invention further provides for protocol state compressor(s) to analyze the protocol specific subset(s) of data to abstract and/or analyze relevant information about the specific protocol without having to strictly process the protocol or preserve protocol state variable(s) in order to analyze the state of the specific protocol. Based upon this analysis, the protocol state compressor(s) can generate event(s) for undesirable state(s) (e.g., error(s) and/or failure(s)) and/or congested state(s) for use by the event correlator/inference engine. Additionally, the protocol state compressor(s) can provide information to the event correlator/inference engine regarding the state of the specific protocol (e.g., success(es)).

A personalized content recommendation system includes a client interface device configured to monitor a user's information data stream. A collaborative filter remote from the client interface device generates automated predictions about the interests of the user. A database server stores personal behavioral profiles and user's preferences based on a plurality of monitored past behaviors and an output of the collaborative user personal interest inference engine. A programmed personal content recommendation server filters items in an incoming information stream with the personal behavioral profile and identifies only those items of the incoming information stream that substantially matches the personal behavioral profile. The identified personally relevant content is then recommended to the user following some priority that may consider the similarity between the personal interest matches, the context of the user information consumption behaviors that may be shown by the user's content consumption mode.