| Patent application number | Description | Published |
|---|
| 20090141891 | DISTRIBUTED SCALABLE CRYPTOGRAPHIC ACCESS CONTROL - Published resources are made available in an encrypted form, using corresponding resource keys, published through resource key files, with the publications effectively restricted to authorized peer systems only by encrypting the resource keys in a manner only the authorized peer systems are able to recover them. In one embodiment, the resource keys are encrypted using encryption public keys of the authorized peer systems or the groups to which the authorized peer system are members. In one embodiment, the encryption public keys of individual or groups of authorized peer systems are published for resource publishing peer systems through client and group key files respectively. Group encryption private keys are made available to the group members through published group key files. Further, advanced features including but not limited to resource key file inheritance, password protected publication, obfuscated publication, content signing, secured access via gateways, and secured resource search are supported. | 06-04-2009 |
| 20090271528 | EFFICIENT CHUNKING ALGORITHM - The present invention provides a method for chunking an object. The method is arranged to provide efficient chunking of objects such that objects can be efficiently updated between a remote machine and a local machine over a network. The chunking algorithm is applicable in networked application such as file synchronization using remote differential compression (RDC) techniques. The chunking algorithm provides enhanced efficiencies by locating chunk boundaries around local maxima. | 10-29-2009 |
| 20100064141 | EFFICIENT ALGORITHM FOR FINDING CANDIDATE OBJECTS FOR REMOTE DIFFERENTIAL COMPRESSION - The present invention finds candidate objects for remote differential compression. Objects are updated between two or more computing devices using remote differential compression (RDC) techniques such that required data transfers are minimized. An algorithm provides enhanced efficiencies for allowing the receiver to locate a set of objects that are similar to the object that needs to be transferred from the sender. Once this set of similar objects has been found, the receiver may reuse any chunks from these objects during the RDC algorithm. | 03-11-2010 |
| 20100077197 | NON-VOLATILE MEMORY CACHE PERFORMANCE IMPROVEMENT - In order to provide a more efficient persistent storage device, one or more long-term storage media are included along with a non-volatile memory. In one embodiment, one portion of the non-volatile memory is used as a write buffer and a read cache for writes and reads to the long-term storage media. Interfaces are provided for controlling the use of the non-volatile memory as a write buffer and a read cache. Additionally, a portion of the non-volatile memory is used to provide a direct mapping for specified sectors of the long-term storage media. Descriptive data regarding the persistent storage device is stored in another portion of the non-volatile memory. | 03-25-2010 |
| 20100325476 | SYSTEM AND METHOD FOR A DISTRIBUTED OBJECT STORE - An improved system and method for flexible object placement and soft-state indexing of objects in a distributed object store is provided. A distributed object store may be provided by a large number of system nodes operably coupled to a network. A system node provided may include an access module for communicating with a client, an index module for building an index of a replicated data object, a data module for storing a data object on a computer readable medium, and a membership and routing module for detecting the configuration of operable nodes in the distributed system. Upon failure of an index node, the failure may be detected at other nodes, including those nodes that store the replicas of the object. These nodes may then send new index rebuilding requests to a different node that may rebuild the index for servicing any access request to the object. | 12-23-2010 |
| Patent application number | Description | Published |
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| 20100184440 | MOBILE DEVICE NETWORK SELECTION - The described implementations relate to automatic network selection in relation to wireless mobile devices. One method can be applied to a mobile device that has both Wi-Fi and cellular capabilities. The method can attempt to identify Wi-Fi network availability for the mobile device. This method also evaluates whether to configure the mobile device to accomplish data communication over an identified Wi-Fi network or a cellular network. | 07-22-2010 |
| 20110238408 | Semantic Clustering - Semantic clustering techniques are described. In various implementations, a conversational agent is configured to perform semantic clustering of a corpus of user utterances. Semantic clustering may be used to provide a variety of functionality, such as to group a corpus of utterances into semantic clusters in which each cluster pertains to a similar topic. These clusters may then be leveraged to identify topics and assess their relative importance, as for example to prioritize topics whose handling by the conversation agent should be improved. A variety of utterances may be processed using these techniques, such as spoken words, textual descriptions entered via live chat, instant messaging, a website interface, email, SMS, a social network, a blogging or micro-blogging interface, and so on. | 09-29-2011 |
| 20110238409 | Semantic Clustering and Conversational Agents - Semantic clustering techniques are described. In various implementations, a conversational agent is configured to perform semantic clustering of a corpus of user utterances. Semantic clustering may be used to provide a variety of functionality, such as to group a corpus of utterances into semantic clusters in which each cluster pertains to a similar topic. These clusters may then be leveraged to identify topics and assess their relative importance, as for example to prioritize topics whose handling by the conversation agent should be improved. A variety of utterances may be processed using these techniques, such as spoken words, textual descriptions entered via live chat, instant messaging, a website interface, email, SMS, a social network, a blogging or micro-blogging interface, and so on. | 09-29-2011 |
| 20110238410 | Semantic Clustering and User Interfaces - Semantic clustering techniques are described. In various implementations, a conversational agent is configured to perform semantic clustering of a corpus of user utterances. Semantic clustering may be used to provide a variety of functionality, such as to group a corpus of utterances into semantic clusters in which each cluster pertains to a similar topic. These clusters may then be leveraged to identify topics and assess their relative importance, as for example to prioritize topics whose handling by the conversation agent should be improved. A variety of utterances may be processed using these techniques, such as spoken words, textual descriptions entered via live chat, instant messaging, a website interface, email, SMS, a social network, a blogging or micro-blogging interface, and so on. | 09-29-2011 |
