The invention discloses a multi-source heterogeneous data entity identification method and system for central connected subgraphs. The method comprises the steps of performing identification on a given graph to discover all the central connected subgraphs, namely obtaining an entity candidate set; and according to the entity candidate set and a preset logic rule, performing filtering and matching on the central connected subgraphs in the entity candidate set to obtain the central connected subgraphs matched with business logic. The system comprises an identification unit and a matching unit. According to the method and the system, multi-source heterogeneous split structured data can be described; the characteristics of good intuitiveness and descriptiveness are achieved; the expression of a relationship among database tables is highlighted; and an efficient and available model basis is provided for the multi-source structured data. Moreover, the entity candidate set in the fused data is found by utilizing a method for searching for the central connected subgraphs, and then entities are further identified, so that the data entities with better expressive meanings are identified.

Multi-source heterogeneous data entity identification method and system for central connected subgraphs

The present invention relates to an autonomic framework bionic data transmission system. The system comprises a center server and a plurality of excitation gateways which are connected with the centerserver; the excitation gateways are configured to allow the client to access the system; the excitation gateways are further configured to generate private key pairs consisting of public keys and private keys, the private keys are stored at the local of the excitation gateways, and the public keys are send to an assigned excitation gateway; the center server comprises an external server and an internal server; the external server comprises a configuration server, an authentication server, an event server and a content server, and the internal server comprises a basic database, an image database, a session management server, a distributed data storage system and a retrieval server. The system considers the attribute information of the data body in the transmission process so as to improvethe control of the user for the data and the safety of the data.

Autonomic framework bionic data transmission system

The invention discloses a honeycomb rectifier data diversion and data conversion method based on a semantic net body The method comprises the steps that (1) data sources are initialized, driving links of different data source data are loaded according to the types of the selected data sources, the data are displayed in a visible page manner, and a data sheet comprising sheet and data field information is obtained; (2) the sheets and the data fields which can be put in public in the data sheet are selected; (3) an OWL/RDF mapping file is generated according to the sheets and the data fields selected in the step (2) and records the sheets and the data fields which are put in public; (4) RDF instance data and an OWL body file are generated correspondingly according to the instance data in each line in the conversion data source of the OWL/RDF mapping file and the concept and attribute relation described in the OWLRDF; (5) the RDF instance data and the OWL body file which are generated by conversion are encrypted, authorized and transmitted to a cloud storage semantic database

Honeycomb rectifier data diversion and data conversion method based on semantic net body

Current virtual reality systems are more immersive than other traditional forms of digital entertainment, but the handheld controllers they use detract from what would otherwise be a truly immersive experience. This paper outlines a project implemented to overcome this issue by creating a spell-casting game in which everything is controlled by the user’s hand gestures. The implemented game made use of optical capture of the user’s hands using a Leap Motion controller attached to the front of a virtual reality headset. The captured gesture data was passed through a neural network for precise gesture classification in real-time, and the correct sequence of classified gestures created a spell effect in the game. The user was able to cast 10 different spells utilizing various combinations of a set of 14 different gestures.

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Immersive Virtual Reality Utilizing Hand Gesture Capture as a Replacement for Traditional Controls

An ontology matching based case search system includes an entity attribute input group module, an input model management module, an ontology matching module, a WordNet term matching library module, a multi-data source module, a heterogeneous data management module, an output ontology set module, and a matching result display module; the ontology matching module can construct a node structure drawing by ontology examples of the heterogeneous data management module according to a built-in structure matching algorithm, calculates the total similarity among nodes through a structure relationship, is connected to the output ontology set module, and transmits the searched ontology examples. The search system inputs the whole case, searches similar cases, and can achieve multi-data source-oriented ontology matching-based case search.

Ontology matching based case search system

Instance matching acts as a significant part of information integration in semantic web research. While ontology matching focuses on the schema level of data, instance matching deals with massive instances objects. Ambiguation is a common problem which may lead to error matching when different instances share the same names or descriptions. To cope with this problem structural approach is used by many matching systems for disambiguation. However, existing structural approach has a hidden problem named 'error propagation' which would affect the precision of matching result. In this paper, we investigate instance matching techniques and propose a new instance matching framework. It is based on a novel structural matching algorithm which calculates similarity separately on sub graphs. The structural information is fully taken advantage of to realize disambiguation and several indexing strategies are used to cut down the computing overhead. We have conducted experiments on instance matching benchmark and results show that our proposed matching approach is comparable to state-of-art systems. And experiment on real dataset has proved the validity of our approach in instance disambiguation.

A Similarity Graph Matching Approach for Instance Disambiguation

Ontology offers rich properties to describe knowledge in information systems. However, ontologies in knowledge-based systems usually suffer from semantic heterogeneities due to distributed developers. Ontology matching is a key solution to the heterogeneity problem in knowledge management. Though state-of-the-art ontology matching systems are able to support diverse ontology matching tasks, the semantic heterogeneity in ontology matching is still the main challenge. In this paper, we propose an element and graph combined matching framework to specifically deal with semantic heterogeneity during ontology matching. Moreover, we also develop an automated ontology matching system and evaluate the system in diverse ontology matching tasks. By using the graph indexing technique, the matching system is scalable with large ontology matching. The experimental results show that the proposed system achieves a good result in highly heterogeneous matching tasks and a comparable result in large ontology matching tasks.

Haojian Zhong

Papers

Ontology matching based case search system

A Similarity Graph Matching Approach for Instance Disambiguation

RMP: An Element-Level and Graph-Level Combined Ontology Matching Framework