Abstract: A method of generating training documents for training a classifying device comprises, with a processor, sampling from a distribution of words in a number of original documents, and creating a number of pseudo-documents from the distribution of words, the pseudo-documents comprising a similar distribution of words as the original documents. A device for classifying textual documents comprises a processor; and a memory communicatively coupled to the processor, the memory comprising a sampling module to, when executed by the processor, determine the distribution of words in a number of original documents, a pseudo-document creation module to, when executed by the processor, create a number of pseudo-documents from the distribution of words, the pseudo-documents comprising a similar distribution of words as the original documents, and a training module to, when executed by the processor, train the device to classify textual documents based on the pseudo-documents.

Abstract: Documents in a document thread include descriptive terms that have weights. An indication indicates when documents in the document thread reach a threshold of weight for the document thread.

Abstract: Systems and methods for clustering a plurality of feature vectors. A hierarchical clustering algorithm is performed on the plurality of feature vectors to provide a plurality of clusters and a cluster similarity measure for each cluster representing the quality of the cluster. Each cluster of the plurality of clusters with a cluster similarity measure meeting a threshold value is accepted. A clustering algorithm is performed on each cluster that fails to meet the threshold value to provide a set of subclusters each having an associated cluster similarity measure. Each subcluster having a cluster similarity measure meeting the threshold value is accepted.

Abstract: To identify similar files in an environment having multiple client computers, a first client computer receives, from a coordinator computer, a request to find files located at the first client computer that are similar to at least one comparison file, wherein the request has also been sent to other client computers by the coordinator computer to request that the other client computers also find files that are similar to the at least one comparison file. In response to the request, the first client computer compares signatures of the files located at the first client computer with a signature of the at least one comparison file to identify at least a subset of the files located at the first client computer that are similar to the at least one comparison file according to a comparison metric. The first client computer sends, to the coordinator computer, a response relating to the comparing.

Abstract: Data processing apparatus comprising: a chunk store containing specimen data chunks, a manifest store containing a plurality of manifests, each of which represents at least a part of a data set and each of which comprises at least one reference to at least one of said specimen data chunks, a sparse chunk index containing information on only some specimen data chunks, the processor being operable to: process input data into input data chunks; identify manifests having at least one reference to one of said specimen data chunks that corresponds to one of said input data chunks and on which there is information contained in the sparse chunk index; and prioritize the identified manifests for subsequent operation.

Abstract: A coating for an object having identifying indicia disposed thereon. An ink layer contacts at least a portion of the identifying indicia. The ink layer obscures the portion when exposed to light within a predetermined wavelength range, and the ink layer reveals a predetermined area of the portion when exposed to light outside of the predetermined wavelength range.

Abstract: A method (200) of identifying a principal document in a document set is provided. An exemplary method includes obtaining a document set comprising a plurality of documents (202) and grouping the plurality of documents into a plurality of clusters based, at least in part, on a textual similarity between each of the plurality of documents (204). The method also includes obtaining one or more descriptive terms corresponding to the plurality of documents, wherein the descriptive terms are terms within the plurality of documents that have been identified as being useful for discriminating between the clusters (206). The method also includes, for each cluster, identifying a subset of descriptive terms based, at least in part, on a prevalence of the descriptive terms within the documents of the cluster (208) and identifying the principal documents in the cluster based, at least in part, on a prevalence of the subset of descriptive terms within each of the documents in the cluster (210).

Abstract: A system and method for data cache management are provided in which a request for access to data is, and a sample value is assigned to the request, the sample value being randomly selected according to a probability distribution. The sample value is compared to another value such as a previously stored sample value, and the data is selectively stored in the cache based on results of the comparison. If the requested data is not in the cache, the sample value may be compared with an extreme one of a plurality of sampled values such as the lowest sampled value. Each of the sampled values may be stored in a database, and the sampled values or the probability distribution may be changed over time to account for frequency of requests.

Abstract: In one embodiment of the present invention, a source point in a supply chain generates a secret and devises a secret sharing scheme that parcels the secret into a number of secret shares. The source point retains at least one secret share, and distributes the remaining secret shares to trusted, intermediate points in the supply chain. The source point then ships a shipment comprising are least one object, and frequently including at least one level of packaging, to a destination point in the supply chain, labeling the object or objects and/or packaging enclosing the object or objects with the retained secret share. Each intermediate point incorporates the secret share obtained by the intermediate point from the source point into the object, packaging enclosing the object, or a label on the object or packaging.

Abstract: A particular data value is represented as a group of segments stored in corresponding entries of a data structure. Additional data values represented by corresponding groups of segments are written into the data structure. A probability of overwriting segments representing the particular data value increases as a number of the additional data values increase. A correct version of the particular data value is retrieved even though one or more segments representing the particular data value has been overwritten.

Abstract: Data processing apparatus comprising: a chunk store containing specimen data chunks, a manifest store containing at least one manifest that represents at least a part of a data set and that comprises at least one reference to at least one of said specimen data chunks, a sparse chunk index containing information on only those specimen data chunks having a predetermined characteristic, the processing apparatus being operable to process input data into input data chunks and to use the sparse chunk index to identify at least one of said at least one manifest that includes at least one reference to one of said specimen data chunks that corresponds to one of said input data chunks having the predetermined characteristic.

Abstract: A package identifier for a package having at least one sub-package is generated. A package identifier generating function is performed on at least one sub-package identifier of the at least one sub-package to generate the package identifier. In addition, the generated package identifier is stored for use in authentication.

Abstract: A method of identifying a fresh document in a document set is provided. The method may include obtaining a query document that is included in a document set comprising a plurality of documents. The method may also include grouping the plurality of documents into a plurality of fine clusters based on a textual similarity between the plurality of documents. The method may also include identifying a target fine cluster within the plurality of fine clusters, the target fine cluster including the query document. The method may also include ordering the documents included in the target fine cluster by time to identify the fresh document. The method may also include generating a query response that includes the fresh document.

Abstract: A computer system that includes a graphical user interface used to organize a group of documents is provided. The system includes a processor that is adapted to execute machine-readable instructions. The system also includes a storage device that is adapted to store data. The data includes a plurality of documents and instructions that are executable by the processor to generate the graphical user interface. The graphical user interface includes a cluster map that includes the results of a clustering algorithm applied to the documents. The graphical user interface also includes a principal documents screen that includes a principal document that is identified by weighting each of the documents in a cluster based, at least in part, on an occurrence of representative terms in the document. The representative terms are terms that have been identified by the clustering algorithm as being more effective for distinguishing between documents that belong to different clusters.

Abstract: A method of identifying a provenance of a document is provided. The method may include obtaining a query document that is included in a document set comprising a plurality of documents. The method may also include grouping the plurality of documents into a plurality of fine clusters based on a textual similarity between the plurality of documents. The method may also include identifying a target fine cluster within the plurality of fine clusters, the target fine cluster including the query document. The method may also include ordering the documents included in the target fine cluster based, at least in part, on metadata associated with each of the documents to identify a source document. The method may also include generating a query response that includes the source document.

Abstract: Embodiments of the present invention pertain to determining an approximate number of instances of an item for an organization. According to one embodiment, instances of items that reside on computer systems associated with the organization are determined. Instances of the same item can reside on different computers and an identification uniquely identifies an item. Random numbers are associated with identifications of the items. An approximate number of instances of the item is determined based on a highest random number associated with the item. The highest random number is the highest of the random numbers that were generated for the instances of the item.

Abstract: One embodiment is a data processing apparatus that has a chunk store containing specimen data chunks, a manifest store containing a plurality of manifests, each of which represents at least a part of previously processed data and includes at least one reference to at least one of the specimen data chunks, and a sparse chunk index containing information on only some specimen data chunks. Input data is processed into a plurality of input data segments. Each manifest of the first set has at least one reference to one of said specimen data chunks that corresponds to one of the input data chunks of a first input data segment. Specimen data chunks corresponding to other input data chunks of the first input data segment are identified by using the identified first set of manifests and at least one manifest identified when processing previous data.

Abstract: Data objects are selectively stored across a plurality of differential data stores, where selection of the differential data stores for storing respective data objects is according to a criterion relating to compression of the data objects in each of the data stores, and where the differential data stores are stored in persistent storage media. Plural requests for accessing the differential data stores are batched, and one of the differential data stores is selected to page into temporary storage from the persistent storage media. The batched plural requests for accessing the selected differential data store that has been paged into the temporary storage are executed.

Abstract: A plurality of differential data stores are stored in persistent storage media. In response to receiving a first request to store a particular data object, one of the differential data stores that are stored in the persistent storage media is selected, wherein selecting the one differential data store is according to a criterion relating to compression of data objects in the differential data stores. The selected differential data store is copied into temporary storage media, where the copying is not delayed after receiving the first request to await receipt of more requests. The particular data object is inserted into the copy of the selected differential data store in the temporary storage media, where the inserting is performed without having to retrieve more data from the selected differential store in the persistent storage media.

Abstract: To identify similar files in an environment having multiple client computers, a first client computer receives, from a coordinator computer, a request to find files located at the first client computer that are similar to at least one comparison file, wherein the request has also been sent to other client computers by the coordinator computer to request that the other client computers also find files that are similar to the at least one comparison file. In response to the request, the first client computer compares signatures of the files located at the first client computer with a signature of the at least one comparison file to identify at least a subset of the files located at the first client computer that are similar to the at least one comparison file according to a comparison metric. The first client computer sends, to the coordinator computer, a response relating to the comparing.