318 results about "Knowledge acquisition" patented technology

A system and method for supporting coordination of resources for events in an organization includes a knowledge component storing a resource-utilization model, the resource-utilization model comprising at least one ontology, each ontology comprising a respective schema and data stored according to the schema; a knowledge acquisition component adapting the resource-utilization model in real-time in response to receiving data from various sources about resource utilization in the organization; a domain reasoner adapting the resource-utilization model based on contents of a modifiable set of rules applied by the organization; and a query endpoint receiving queries about resources for events and responding to the queries based on the resource-utilization model.

A knowledge management system captures, stores, manages, and applies rules for modeling geometric objects and related non-geometric attributes. The knowledge management system controls a computer-aided design system for modeling a geometric structure. The knowledge management system includes a knowledge management application in communication with the computer-aided design system through an application program interface. The knowledge management system also includes a central database managed by a knowledge storage application for maintaining rules and other related information. The knowledge management system also includes a knowledge acquisition application for generating rule programs for storage in the central database. The rules can relate to geometric and non-geometric attributes of the model.

The method comprises: using a sensor to collect the characteristic signals; the collected signals about each kind of running state are sent to the data processing module; after processed, the signals are sent to the computer system; said computer system comprises a device database, a symptom event database, a diagnosis knowledge database; a device database and signal analysis module, a symptom acquiring module, a diagnostic reasoning module, and a diagnosis explaining module; the software of the data processing module makes data exchange; the symptom event database exchanges data with the diagnostic module, data processing module; the diagnostic knowledge exchanges the data with the failure processing module, knowledge acquiring module and data processing module.

A method for structuring specialist system based on knowledge discovery includes forming new knowledge base unit by knowledge obtained from inference mechanism and knowledge learned from failure and mistakes, adding new knowledge obtaining-channel on said system, setting knowledge discovery process module in databank and setting knowledge discovery-creating mechanism and model in knowledge base.

The invention provides a computer fault management system based on an expert system method, which comprises a data acquisition unit (1), a fault event generation module (2), a fault diagnosis engine (3), a knowledge base (4), a knowledge acquisition module (5), a fault isolation module (6), a fault recovery module (7), a fault early-warning module (8), a log service module (9), a fault management registration module (10) and a human-computer interaction interface (11); and a system administrator monitors and manages the data acquisition unit (1), the fault event generation module (2), the fault diagnosis engine (3), the knowledge base (4), the fault isolation module (5), the fault recovery module (6), the fault early-warning module (7) and the log service module (8) through the human-computer interaction interface (11), and accesses an intelligent editor provided by the knowledge acquisition module (5) through the human-computer interaction interface (11).

A system and method that translates sentences of natural language text into sets of axioms of formal logic that are consistent with parses resulting from NLP and acquired constraints as they accumulate. The system and method further present these axioms so as to facilitate further disambiguation of such sentences and produces axioms of formal logic suitable for processing by automated reasoning technologies, such as first-order or description logic suitable for processing by various reasoning algorithms, such as logic programs, inference engines, theorem provers, and rule-based systems.

In an automated Question Answer (QA) system architecture for automatic open-domain Question Answering, a system, method and computer program product for predicting the Lexical Answer Type (LAT) of a question. The approach is completely unsupervised and is based on a large-scale lexical knowledge base automatically extracted from a Web corpus. This approach for predicting the LAT can be implemented as a specific subtask of a QA process, and / or used for general purpose knowledge acquisition tasks such as frame induction from text.

The invention provides a building method used for a knowledge obtaining model in a knowledge graph. The method comprises the steps of constructing a first training set consisting of multiple text sentences as input data and a relationship between any two entities in each sentence in the knowledge graph, as a classification result, and training a first neural network; constructing a second trainingset consisting of triples in multiple knowledge graphs, and training a second neural network; by taking input data vectors obtained in the second neural network as attention features of the first neural network, building a relationship extraction model; by taking input data vectors obtained in the first neural network as attention features of the second neural network, building a knowledge representation model; and fusing the relationship extraction model and the knowledge representation model to obtain the knowledge obtaining model in the knowledge graph. According to the method provided bythe invention, the two task models of knowledge representation and relationship extraction are integrated at the same time, and the features of the knowledge graph and free texts can be comprehensively extracted, so that the model stability and accuracy are improved.

Text is extracted from and information resource such as documents, emails, relational database tables and other digitized information sources. The extracted text is processed using a decomposition function to create. Nodes are a particular data structure that stores elemental units of information. The nodes can convey meaning because they relate a subject term or phrase to an attribute term or phrase. Removed from the node data structure, the node contents are or can become a text fragment which conveys meaning, i.e., a note. The notes generated from each digital resource are associated with the digital resource from which they are captured. The notes are then stored, organized and presented in several ways which facilitate knowledge acquisition and utilization by a user.

A multiple integration hypothesis C / A code acquisition system resolves bit boundaries using parallel correlators providing magnitude hypotheses during acquisition to reduce losses over the 20 ms integration period to improve the performance and sensitivity of C / A code receivers to achieve low C / No performance using inexpensive, imprecise oscillators and long noncoherent dwell periods, well suited for in-building, multipath, and foliage attenuated GPS signaling applicable to E911 communications with several dB of additional improvement in receiver sensitivity due to the ability to detect bit synchronization during acquisition.

An automated diagnostic system uses Bayesian networks to diagnose a system. Knowledge acquisition is performed in preparation to diagnose the system. An issue to diagnose is identified. Causes of the issue are identified. Subcauses of the causes are identified. Diagnostic steps are identified. Diagnostic steps are matched to causes and subcauses. Probabilities for the causes and the subcauses identified are estimated. Probabilities for actions and questions set are estimated. Costs for actions and questions are estimated.

A solution that improves a user's experience while surfing the Internet. An intermediate device resides logically between a browsing device and content available via the Internet. As responses to content requests from browsing devices are received from a content server, browser links are identified and modified, disabled or covered for example. The intermediate device also creates a browser link to a compound browser object(s) that is created and stored at the intermediate device. This created browser link invokes code at the intermediate device to upload the compound browser object(s). The intermediate device obtains these compound browser objects by obtaining content associated with the identified browser links either from a content server, a local cache or knowledge of its existence eat the browser device.

In an automated Question Answer (QA) system architecture for automatic open-domain Question Answering, a system, method and computer program product for predicting the Lexical Answer Type (LAT) of a question. The approach is completely unsupervised and is based on a large-scale lexical knowledge base automatically extracted from a Web corpus. This approach for predicting the LAT can be implemented as a specific subtask of a QA process, and / or used for general purpose knowledge acquisition tasks such as frame induction from text.

The invention discloses a knowledge map construction method for medical images, belonging to the field of knowledge maps. The construction process includes a step of knowledge representation with a framework theory representation method, a step of knowledge acquisition, wherein the knowledge sources of entity, attribute and attribute value extraction is unstructured data, a step of knowledge fusion with the integration of acquired new knowledge and the elimination of ambiguity, a step of knowledge processing with the knowledge reasoning and quality assessment of the data which is subjected tothe knowledge fusion and the adding of qualified data to a knowledge map, and a step of knowledge update with the update of the knowledge map according to the update and development of medical image knowledge. According to the characteristics of the medical image knowledge, and the knowledge acquisition rate is greatly improved with the unstructured data such as textbooks and academic journals asa source of knowledge.

The invention discloses a fault diagnosis expert system based on a decision tree for an industrial Ethernet network. Firstly, an expert system comprising a knowledge base, an inference engine, a knowledge base management module, a knowledge acquisition module, an explanation facility and a control center is established; secondly, the knowledge base is utilized to contact the inference engine and the control center to obtain data required by the modules for storing a diagnosis rule, various pieces of data of the system and an intermediate result generated during the system diagnosis period; thirdly, comparison, commonly called as matching, is carried out between a condition part of a rule base and a content of a global data base through the inference engine, if matching is successful, a conclusion part is displayed, the global data base is modified according to an action part of an enable rule, the changed global data base can trigger a new rule, so that problem solving proceeds to the next state, and so forth, one problem is finally solved; and lastly, post processing is carried out through the inference engine, a new knowledge base is updated by the control center, so that the expert system is gradually improved.

A system and method to organize information on the internet for rapid and organized retrieval. Registrants of websites can register URLs by specifying the URL and associated descriptors. A bot automatically determines URLs and metadata associated with the registered URL. The URLs and descriptors and / or metadata form a URL database. Search terms entered by users can be indexed against a knowledge database using one or more retrieval algorithms to provide keyword associations. The knowledge database further includes a knowledge acquisition and retrieval system and method that include at least one first memory segment, and a distinct second memory segment, wherein elements of the at least one first memory segment reciprocally associate to elements of the second memory segment. Registrants can modify the knowledge database to incorporate non-traditional associations. The search term, keyword associations, and URL associations provide an organized search result that includes subcategories and cross-categories of information that can be further searched by the user. URL links can be provided in the search results.

The invention relates to a system and method for knowledge capture using multi-relational ontologies. The system may enable an ontology service provider to ascertain the scope of an entity's knowledge capture needs, create one or more base ontologies from publicly available sources, and incorporate the entity's private data into one or more value-added custom ontologies.

A knowledge acquisition system and artificial cognitive declarative memory model to store and retrieve massive student learning datasets. A Deep Academic Learning Intelligence system for machine learning-based student services provides monitoring and aggregating performance information and student communications data in an online group learning course. The system uses communication activity, social activity, and the academic achievement data to present a set of recommendations and uses responses and post-recommendation data as feedback to further train the machine learning-based system.

The invention discloses a Web-based domain knowledge map construction system and method. The system comprises a knowledge modeling subsystem, a data and entity link subsystem, a human assisted labeling subsystem and a knowledge visualization subsystem, wherein the knowledge modeling subsystem is sued for obtaining an original knowledge model according to a preset data resource, and receiving an operation instruction of an operation interface so as to construct a data mode of a knowledge map to obtain a knowledge model; the data and entity link subsystem is used for extracting knowledges according to multiple types of data and storing the extracted knowledges into the knowledge map; the human assisted labeling subsystem is used for receiving a user labeling instruction so as to change the knowledge map according to the user labeling instruction; and the knowledge visualization subsystem is used for visually displaying the knowledge model, a dynamic link between the knowledge model and an entity and the changed knowledge map. The system is capable of simply and conveniently completing the work such as knowledge modeling, knowledge obtaining and knowledge visualization, so that the domain knowledge map construction difficulty is greatly reduced and benefit is brought to enhance the accuracy of domain knowledge maps.

Embodiments relate to authoring, consuming, and exploiting dynamically adaptive e-learning courses created using novel, embedded datagraph structures, including course macrostructures with embedded lesson microstructures and practice microstructures. For example, courses can be defined by nodes and edges of directed graph macrostructures, in which each node includes one or more directed graph microstructures for defining lesson and practice step objects of the courses. The content and attributes of the nodes and edges can adaptively manifest higher level course flow relationships and lower level lesson and practice flow relationships. Embodiments can exploit such embedded datagraph structures to facilitate dynamic course creation and increased course adaptability; improved measurement of student knowledge acquisition and retention, and of student and teacher performance; enhanced monitoring and responsiveness to student feedback; and access to, exploitation of, measurement of, and / or valuation of respective contributions; etc.

The present invention relates to a system and method using hybrid spectral compression and cross correlation signal processing of signals of opportunity, which may include Global Navigation Satellite System (GNSS) as well as other wideband energy emissions in GNSS obstructed environments. Combining spectral compression with spread spectrum cross correlation provides unique advantages for positioning and navigation applications including carrier phase observable ambiguity resolution and direct, long-code spread spectrum signal acquisition. Alternatively, the present invention also provides unique advantages for establishing the validity of navigation signals in order to counter the possibilities of electronic attack using spoofing and / or denial methods.

The invention relates to the technical field of disaster emergency processing, in particular to a knowledge graph construction method based on a disaster scene, which comprises the following steps: constructing a ontology meta-language model of a knowledge graph in a mode layer of a knowledge graph database; acquiring data information of the disaster scene from one or more disaster data sources; performing knowledge fusion on the acquired data information, and eliminating contradiction and ambiguity between the data; conducting knowledge reasoning on the data information obtained after knowledge fusion; and storing the data information after knowledge reasoning into a data layer of a knowledge map database corresponding to the ontology meta-language model. According to the knowledge graphconstruction method based on the disaster scene, from the perspective of machine cognition, the knowledge graph is combined with disaster scene situation awareness and understanding, connotation and semantics of multi-source heterogeneous information are studied, a disaster scene information fusion method is designed, and support can be provided for engineering application.

Embodiments measure knowledge levels of students with respect to knowledge entities as they proceed through a course datagraph macrostructure, and dynamically adapt aspects of the macrostructure (and / or its embedded microstructures) to optimize knowledge acquisition of the students in accordance with their knowledge level. For example, a course consumption platform can parse the macrostructure and embedded microstructures to identify next microstructures to present to the student in such a way that dynamically adapts knowledge entities of the course to a student as a function of the student's present knowledge level associated with the student and difficulty levels of the presented microstructures. The platform can dynamically compute an updated knowledge level for the student throughout acquisition of the knowledge entity as a function of the student's responses to the microstructures, the student's present knowledge level at the time of the responses, and the difficulty levels of the presented microstructures.

The present invention tightly integrates and significantly leverages media capture systems to realize a ubiquitous collaborative multi-user environment, referred to as TalkingPaper, taking full advantages of what each unique medium can offer and further enhancing their respective functions and utilities. The invention comprises a paper-pen based knowledge capture subsystem A and a knowledge processing subsystem B. A user uses a subsystem A compliant pen to sketch on a piece of subsystem A enabled paper. The sketching activity, speech and gesture are recorded by the pen, which sends the captured data to a multi-threaded application server of subsystem B for further processing. The server converts and indexes the data to associate and synchronize each line stroke with corresponding audio time frames and enable the content interaction. Thus, users can easily find, select, and replay a session with synchronized speech, text, and video to understand the rationale behind certain ideas or decisions.

The invention discloses a knowledge map construction method based on a medical domain website, which is characterized in that the method comprises the following steps: 1, collecting entities, entity attributes and corpus according to a preset data source of the medical domain; 2, extracting relationships between entity based on a BiLSTM (bidirectional long-short-term memory network) model; Step 3:performing knowledge fusion and map generation. To provide effective, complete and reliable knowledge of the disease at the knowledge level; Beneficial effects of intelligent question answering in the field of auxiliary medicine and semantic search and query understanding in the field.