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Patent Application Titled "System and Methods Thereof for Generation of Taxonomies Based on an Analysis of Multimedia Content Elements" Published...

August 12, 2014



Patent Application Titled "System and Methods Thereof for Generation of Taxonomies Based on an Analysis of Multimedia Content Elements" Published Online

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- According to news reporting originating from Washington, D.C., by VerticalNews journalists, a patent application by the inventors Raichelgauz, Igal (Ramat Gan, IL); Odinaev, Karina (Ramat Gan, IL); Zeevi, Yehoshua Y. (Haifa, IL), filed on March 25, 2014, was made available online on July 31, 2014.

The assignee for this patent application is Cortica, Ltd.

Reporters obtained the following quote from the background information supplied by the inventors: "With the abundance of multimedia data made available through various means in general and, in particular, through the Internet and world-wide web (WWW), there is a need for effective ways of searching for and managing such multimedia data. Searching, organizing and managing multimedia data in general and, in particular, video data may be challenging at best due to the difficulties associated with representing and comparing the information embedded in the video content, and further due to the scale of information that needs to be checked. Moreover, when it is necessary to find a content of a video by means of textual query, prior art solutions revert to analyzing various metadata that textually describe the content of the multimedia data. However, such content may be abstract and complex by nature, and is not necessarily adequately defined by the existing and/or attached metadata.

"The rapid increase in multimedia databases, accessible for example through the Internet, calls for the application of new methods of representing information embedded in video content. Searching for multimedia in general and for video data in particular is challenging due to the huge amount of information that must have been previously indexed, classified, and clustered. Moreover, prior art techniques revert to model-based methods to define and/or describe multimedia data. However, by its very nature, the structure of such multimedia data may be too abstract and/or complex to be adequately represented by metadata. The greatest difficulty arises in cases where the target sought for multimedia data is not adequately defined in words or by respective metadata of the multimedia data. For example, it may be desirable to locate a car of a particular model in a large database of video clips or segments. In some cases, the model of the car would be part of the metadata, but in many cases it would not. Moreover, the car may be shown at angles different from the angles of a specific photograph of the car that is available as a search item. Similarly, if a piece of music, as in a sequence of notes, is to be found, it is not necessarily the case that in all available content the notes are known in their metadata form, or for that matter, the search pattern may just be a brief audio clip.

"A system implementing a computational architecture (hereinafter 'the Architecture') that is based on a PCT patent application publication number WO2007/049282 and published on May 3, 2007, entitled 'A Computing Device, a System and a Method for Parallel Processing of Data Streams', assigned to common assignee, is hereby incorporated by reference for all the useful information it contains. Generally, the Architecture consists of a large ensemble of randomly, independently generated, heterogeneous processing cores, mapping in parallel data-segments onto a high-dimensional space and generating compact signatures for classes of interest.

"Searching multimedia data has been a challenge in the past several years and has therefore received considerable attention. Early systems would take a multimedia data element in the form of, for example, an image, compute various visual features from it and then search one or more indexes to return images with similar features. In addition, values for these features and appropriate weights reflecting their relative importance could be also used. Searching and indexing techniques have improved over time to improve handling of various types of multimedia inputs. However, due to the exponential growth of the use of the Internet and the multimedia data available there, these prior art systems have become less effective in handling the multimedia data, due to the vast amounts already existing, as well as the speed at which new ones are added.

"Searching has therefore become a significant challenge and even the addition of metadata to assist in the search has limited functionality. Firstly, metadata may be inaccurate or not fully descriptive of the content contained within the multimedia data, and secondly, not every piece of multimedia data can be described accurately enough by a sequence of textual metadata. A query model for a search engine has some advantages, such as comparison and ranking of images based on objective visual features, rather than on subjective image annotations. However, the query model has its drawbacks as well. Certainly when no metadata is available and only the multimedia data needs to be used, the process requires significant effort. Those skilled in the art will appreciate that there is no known intuitive and automated way of describing multimedia data in a manner consistent with an average user's conception of the data. Therefore, a user's perception or conceptual understanding of the multimedia data may significantly differ from the way it is actually stored and manipulated by a search engine.

"The current generation of web applications has become more and more effective at aggregating massive amounts of data of different multimedia content, such as, pictures, videos, clips, paintings and mash-ups. Such applications are capable of slicing and dicing components of multimedia content in different ways, as well as searching the content and displaying it in an organized fashion by using, for example, concept networks. A concept network may enable understanding of a multimedia data based on its related concept. However, current art is unable to add any real 'intelligence' to the mix, i.e., no new knowledge is extracted from the multimedia data that are aggregated by such systems. Moreover, the systems tend to be non-scalable due to the vast amounts of data they have to handle. This inherently hinders these systems' ability to provide high quality searching for multimedia content."

In addition to obtaining background information on this patent application, VerticalNews editors also obtained the inventors' summary information for this patent application: "Certain embodiments disclosed herein include a method for generating taxonomies based on analysis of at least one multimedia data element (MMDE). The method comprises receiving the at least on MMDE; generating at least one signature for the at least one received MMDE; matching the at least one generated signature to a plurality of clusters to find at least one matching cluster; associating the at least one generated signature with each of the at least one matching cluster; and analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.

"Certain embodiments disclosed herein also include a system for generating concept structures. The system comprises an interface to a network for receiving a request to create a new concept structure, wherein the request includes at least a multimedia data element (MMDE) related to the new concept structure; a processor; and a memory connected to the processor, the memory contains instructions that when executed by the processor, configure the system to: receive the at least one MMDE; generate at least one signature for the at least one received MMDE; match the at least one generated signature to a plurality of clusters to find at least one matching cluster; associate the at least one generated signature with each of the at least one matching cluster; and analyze the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.

BRIEF DESCRIPTION OF THE DRAWINGS

"The subject matter disclosed herein is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other objects, features and advantages of the disclosed embodiments will be apparent from the following detailed description taken in conjunction with the accompanying drawings.

"FIG. 1 is a diagram of a DCC system for creating concept structures.

"FIG. 2 is a flowchart illustrating the operation of the patch attention processor of the DCC system.

"FIG. 3 is a block diagram depicting the basic flow of information in a large-scale video matching system.

"FIG. 4 is a diagram showing the flow of patches generation, response vector generation, and signature generation in a large-scale speech-to-text system.

"FIG. 5 is a flowchart illustrating the operation of the clustering processor of the DCC system.

"FIG. 6 is a flowchart illustrating the operation of the concept generator of the DCC system.

"FIG. 7 is a flowchart illustrating the operation of taxonomies generation in accordance with an embodiment."

For more information, see this patent application: Raichelgauz, Igal; Odinaev, Karina; Zeevi, Yehoshua Y. System and Methods Thereof for Generation of Taxonomies Based on an Analysis of Multimedia Content Elements. Filed March 25, 2014 and posted July 31, 2014. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&u=%2Fnetahtml%2FPTO%2Fsearch-adv.html&r=697&p=14&f=G&l=50&d=PG01&S1=20140724.PD.&OS=PD/20140724&RS=PD/20140724

Keywords for this news article include: Information Technology, Information and Data Tagging.

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Source: Information Technology Newsweekly


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