News Column

Patent Application Titled "System and Method of Reduction of Irrelevant Information during Search" Published Online

June 18, 2014



By a News Reporter-Staff News Editor at Defense & Aerospace Week -- According to news reporting originating from Washington, D.C., by VerticalNews journalists, a patent application by the inventors Bahrami, Ali (Sammamish, WA); Yuan, Jun (Sammamish, WA), filed on November 26, 2012, was made available online on June 5, 2014.

The assignee for this patent application is The Boeing Company.

Reporters obtained the following quote from the background information supplied by the inventors: "The present disclosure relates generally to improved data manipulation techniques and, in particular, to a system and method for reducing irrelevant information generated during search activities by filtering out irrelevant results based on association of a data object's values to values of contexts associated with the data object.

"Parties searching for specific information, particularly during ongoing events when real time information is readily available and abundant, may be inundated with input from a plurality of sources. However, much of the input may have no relevance or value at the moment given the immediate and concentrated nature of the task or mission. Additionally, recent years have seen an exponential growth in the quantity and diversity of readily available information sources. Information sources have proliferated in quantity, depth and diversity because of linkage of databases using evolving technologies such as data tags and data mining. While these developments may be beneficial in many respects, the increased availability of real time information may cause difficulty for parties operating under time constraints and seeking actionable and timely information needed to complete a specific task. Such difficulty may be more pronounced when the heavy volume of received input concerns events taking place concurrently, and a party faced with making decisions is relying primarily or solely on the incoming rush of information.

"In addition to the expanding quantity of information stored in databases and in other storage locations such as cloud-based media, the sheer volume of real-time and near real-time information about ongoing events has also increased exponentially in recent years. Internet-based video and online social networking and microblogging services are examples of this widely accessible content. The growth of interactive and user-collaborative media associated with the advent of the Web 2.0 internet has spawned an explosion of content. Such content is easily and readily accessible at minimal or no cost from public sources. However, receiving and processing such available information may be burdensome due to the sheer volume of the information and raw format with which it is made available. Even a large organization with significant processing and storage capacity may be overwhelmed by the quantity of information available. Much of the information may not be relevant to the organization's immediate objective which may be to take action in a currently developing and dynamic situation.

"Cross-correlation of information has historically been a manual process. However, incoming data may not be analyzed rapidly enough for timely action, and most such analyses are performed in isolation. Parties participating in or overseeing such events and charged with making decisions about allocating resources or moving personnel may benefit from tools that quickly discard information that is not immediately relevant. Filtering out irrelevant information may increase the agility and accuracy of decision making. Filtering out irrelevant information also may decrease complexity, present fewer and clearer choices, and reduce expense arising from direct management costs and wasted resources. Filtering out irrelevant information also may reduce opportunity costs associated with disregarding a good choice. Thus, effective new techniques for filtering out irrelevant information are considered desirable."

In addition to obtaining background information on this patent application, VerticalNews editors also obtained the inventors' summary information for this patent application: "The illustrative embodiments provide for a system. The system includes a context-entity factory configured to build a data model defining an ontology of data objects that are context-aware, the data model further defining metadata tags for the data objects. The system also includes a storage device storing the data objects as stored data objects, the storage device further storing associated contexts for corresponding ones of the stored data objects. The system also includes a reduction component configured to capture a current context value of a first data object defined in the ontology of data objects, the reduction component further configured to compare the current context value of the first data object with stored values of the associated contexts, and wherein when the current context value does not match a particular stored value of a particular associated context in the associated contexts, the reduction component is further configured to remove a corresponding particular stored data object and the particular associated context from the stored data objects.

"The illustrative embodiments also provide for a method using a computer in conjunction with a non-transitory computer readable storage medium. The method comprises performing, using a processor, text mining of activity patterns on a first body of data comprising open-source unstructured text. The method also comprises performing, using the processor, constraint-based mining of activity patterns on a second body of data drawn from multiple heterogeneous sources. The method also comprises submitting, using the processor, output of text mining of activity patterns and output of constraint-based mining of activity patterns to at least one contextual query engine. The method also comprises building, using the at least one contextual query engine, at least one contextual query filter. The method also comprises providing, using the processor, the contextual query filter to at least one information mashup application for combination with at least one semantic query template. The method also comprises combining, using the processor and the at least one information mashup application, the at least one contextual query filter and the at least one semantic query template to produce at least one refined semantic query.

"The illustrative embodiments also provide for another system. The system may include a computer comprising a bus, a processor connected to the bus, and a memory connected to the bus. The memory stores program code which, when executed by the processor, performs a computer-implemented method. The program code comprises program code for performing, using the processor, text mining of activity patterns on a first body of data comprising open-source unstructured text. The program code also comprises program code for performing, using the processor, constraint-based mining of activity patterns on a second body of data drawn from multiple heterogeneous sources. The program code also comprises program code for submitting, using the processor, output of text mining activity patterns and output of constraint-based mining of activity patterns to at least one contextual query engine. The program code also comprises program code for building, using the at least one contextual query engine, at least one contextual query filter. The program code also comprises program code for providing, using the processor, the at least one contextual query filter to at least one information mashup application for combination with at least one semantic query template. The program code also comprises program code for combining, using the processor and the information mashup application, the at least one contextual query filter and the at least one semantic query template to produce at least one refined semantic query.

"The features, functions, and benefits may be achieved independently in various embodiments of the present disclosure or may be combined in yet other embodiments in which further details can be seen with reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

"The novel features believed characteristic of the illustrative embodiments are set forth in the appended claims. The illustrative embodiments, however, as well as a preferred mode of use, further objectives and features thereof, will best be understood by reference to the following detailed description of an illustrative embodiment of the present disclosure when read in conjunction with the accompanying drawings, wherein:

"FIG. 1 is an illustration of a block diagram of a system for reduction of irrelevant information during search, in accordance with an illustrative embodiment;

"FIG. 2 is an illustration of a block diagram of a method for reduction of irrelevant information during search, in accordance with an illustrative embodiment;

"FIG. 3 is an illustration of a block diagram of a workflow, in accordance with an illustrative embodiment;

"FIG. 4 is an illustration of a block diagram of another workflow, in accordance with an illustrative embodiment;

"FIG. 5 is an illustration of a block diagram of another workflow, in accordance with an illustrative embodiment; and

"FIG. 6 is an illustration of a data processing system, in accordance with an illustrative embodiment."

For more information, see this patent application: Bahrami, Ali; Yuan, Jun. System and Method of Reduction of Irrelevant Information during Search. Filed November 26, 2012 and posted June 5, 2014. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&u=%2Fnetahtml%2FPTO%2Fsearch-adv.html&r=718&p=15&f=G&l=50&d=PG01&S1=20140529.PD.&OS=PD/20140529&RS=PD/20140529

Keywords for this news article include: The Boeing Company, Aerospace and Defense Companies.

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Source: Defense & Aerospace Week


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