Hewlett-packard Development Company, L.p.

A Marie Vans

Steven J Simske

Malgorzata M Sturgill

Carl Staelin

Ron Maurer

Marcelo Aita Riss

Mark Jacobsen

Udi Chatow

Mick Keyes

Kristin M Smith

Vernica Rares

Julie E Hurley

An example system includes a stage identification portion to determine a stage in a progression of a progressive identifier, and an identifier encoding portion to encode or read the progressive identifier. A number or percentage of bits of the progressive identifier encoded, or read as encoded, by the identifier encoding portion is uniquely associated with the stage in the progression.

Progressive identifier

Example embodiments disclosed herein relate to generating a regressive information object. Information is encoded into an information object at states in a workflow. Information is encoded such that information encoded in a last state in the workflow is readable by an information object reader and information encoded in states prior to the last state is not readable by the information object reader.

Generating a regressive information object

Examples disclosed herein relate to item identifier assignment. For example, a processor may create a mass serialization scheme to provide a list of item identifiers to allow a subset of the identifiers to be knocked out. Each item identifier may associated with multiple containers, and each container may include two item identifiers relating to the sequence of item identifiers included within the container.

Item identifier assignment

Functional summarization of non-textual content based on a meta-algorithmic pattern is disclosed. One example is a system including a converter, a plurality of summarization engines and/or meta-algorithmic patterns, an extractor, and an evaluator. The converter converts the non-textual content into a plurality of tokens. Combinations of summarization engines and/or meta-algorithm patterns are applied to the plurality of tokens to provide a meta-summary. The extractor extracts at least one summarization term from the meta-summary, and at least one class term for each given class of a plurality of classes of non-textual content. The evaluator determines similarity values of the non-textual content over each given class, each similarity value indicative of a similarity between the at least one summarization term and the at least one class term for each given class. The selector selects a class of the plurality of classes, the selecting based on the determined similarity values.

Functional summarization of non-textual content based on a meta-algorithmic pattern

In example implementations, a plurality of re-structured version of texts is generated for each one of a plurality of different documents by applying a plurality of text summarization methods to each one of the plurality of different documents. An effectiveness score is calculated for each one of the plurality of text summarization methods to determine the text summarization method with the highest effectiveness score for an application. The plurality of re-structured versions of text for each one of the plurality of different documents that is generated by the text summarization method that has the highest effectiveness score is stored to be used in the application.

Text restructuring

One example is a system including a plurality of combinations of summarization engines and/or meta-algorithmic patterns used to combine a plurality of summarizers, an extractor, an evaluator, and a selector. Each of the plurality of combinations of summarization engines and/or meta-algorithmic patterns receives content to provide a meta-summary of the content. The extractor generates a collection of search queries based on the content. The evaluator determines a similarity value of each combination of summarization engines and/or meta-algorithmic patterns for the collection of search queries. The selector selects an optimal combination of summarization engines and/or meta-algorithmic patterns based on the similarity value.

Data extraction based on multiple meta-algorithmic patterns

Examples disclosed herein relate to creating a data bearing image related to a compilation and position. In one implementation, a processor tags elements of a compilation with different data bearing images such that the data bearing images include a first information channel related to an identifier associated with the compilation and a second information channel related to relative position information within the compilation of the respective element. The processor may output information related to the compilation and tagged elements.

Data bearing image related to a compilation and position

Example embodiments disclosed hereto relate to generating a regressive information object. Information is encoded into an information object at states in a workflow. Information is encoded such that information encoded in a last state in the workflow is readable by an information object reader and information encoded in states prior to the last state is not readable by the information object reader.

Systems and methods for generating an incremental information object with an embedded information region (IIOEIR) are provided. A method includes analyzing an IIOEIR to determine a first code, wherein the IIOEIR includes a plurality of tiles, and wherein a first set of the plurality of tiles includes a first code and a second set of the plurality of tiles includes a second code. The first code is confirmed, and, if the confirmation succeeds, generating a new code comprising a bitstream, overwriting the bitstream onto the first region. A new second code is generated, wherein the new second code is related to the first code, and the new second code is overwritten onto a second region.

Incremental information object with an embedded information region

Systems and methods for generating an incremental information object (IIO) from an information object (IO). The method includes analyzing an IO to identify code, wherein the IO is made up of a number of tiles, and wherein the tiles make up a code. The method also includes confirming the code. If the code is successfully confirmed, the method further includes modifying the IO by adding binary information IO the IO through the use of color scales that are not recognizable by an optical IO reader, generating a new progressive code comprising a bitstream, and overwriting the bitstream on the tiles.

Generating an incremental information object

Systems and methods for adapting an incremental information object (IIO) to accommodate a change in a workflow are provided. A method includes analyzing an IIO, wherein the IIO comprises a plurality of tiles, and wherein the plurality of tiles comprise a code. The code is confirmed and, if the confirmation is successful, a determination is made as to whether the workflow has changed. If the workflow has changed the IIO is modified to change the information density of the IIO, a new code comprising a bitstream is generated, and the bitstream is overwritten on the plurality of tiles.

Adapting an incremental information object

Systems and methods for generating a dual deterrent information object (IIO) are provided. A method includes analyzing a dual deterrent IIO to determine a first code, wherein the dual deterrent IIO comprises an IIO comprising a plurality of tiles and an associated mark, wherein each tile in the plurality of tiles represents a data element encoded by color, intensity, or both, and the associated mark comprises information related to the IIO. The first code is confirmed, and, if the first code passes the confirmation a new code comprising a bitstream is generated. The bitstream is overwritten on the plurality of tiles, wherein the dual deterrent IIO is the same size after writing of the bitstream. A new associated mark related to the dual deterrent IIO is generated and the associated mark is overwritten with the new associated mark.

Dual deterent incremental information object

A method for tracking customer loyalty information using an incremental information object (IIO) includes capturing an information object (IO), wherein the IO include a number of tiles, and wherein the number of tiles include a standard code. The method also includes analyzing the IO to identify the standard code and analyzing the IO to determine if the IO is an IIO containing a progressive code, wherein the progressive code does not interfere with the reading of the standard. The method further include confirming the progressive code and, if the progressive code is successfully confirmed, obtaining customer loyalty data from the progressive code within the IIO.

Tracking customer loyalty information using an incremental information object

A system and method of removing background noise from a digital image of a scanned document is described. The system and method is a reversible background noise removal technique that allows a user to select whether background noise is removed or not. In addition, since the present invention divides the background noise removal operations into a two phase process, the overall efficiency of the system and method are significantly improved.

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Fort Collins, CO, United States of America

A Marie Vans