US Agency: Search Engines Must Clearly Label Ads

The US Federal Trade Commission has issued a warning to search engines that they need to clearly mark all results that are advertisements. The FTC issued letters 24 June 2013 to firms including AOL, Bing, DuckDuckGo, Google, and Yahoo—plus companies offering specialized search in areas such as local businesses, travel, and shopping—stating that they need to clearly distinguish between paid advertising and routine search results. The agency said paid search results have become increasingly less distinguishable as advertising. Search engine companies, particularly Google, have recently faced similar complaints from European government agencies. The FTC can levy fines for noncompliance with regulations regarding deceptive advertisements. (http://www.siliconvalley.com/news/ci_23542318/google-yahoo-microsoft-told-label-ads-better-search)(CNET)(United States Federal Trade Commission)

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Smart search engines for news videos

Jan. 7, 2013 — Searching for video recordings regularly pushes search engines to their limit. The truth of the matter is that purely automatic algorithms are not enough; user knowledge has to be harnessed, too. Now, researchers are making automated engines smarter.

Anyone who has visited one of the big online video portals or TV broadcasters’ media libraries to search for a video clip is already familiar with the search engines tasked with seeking out and flagging video footage. However, these engines have their weaknesses. Their results are based on automatic search algorithms that often go by text-based information alone. Although they can be used to locate and identify videos, a comparison of individual sequences is still very difficult. To make search engines even smarter, the Fraunhofer Institute for Digital Media Technology IDMT in Ilmenau has developed a piece of software called “NewsHistory” that will now make full use of user knowledge as well. Researchers will be presenting an initial demonstration version of the smart video search engine at the CeBIT trade fair in Hannover.

Technology learns from users

“NewsHistory provides users with search algorithms, a data model and a web-based user interface so that they can locate identical sequences within various news videos,” explains Patrick Aichroth from Fraunhofer IDMT. He is responsible for coordinating the institute’s R&D work within the EU’s CUbRIK project. Here, researchers are harnessing user knowledge to optimize and extend the capabilities of automated analysis techniques. “The search engine learns from each individual user, allowing it to keep improving search results. Not only does this improve the quality of results, but the resources needed to undertake the analysis are also cut down,” Aichroth continues.

NewsHistory allows each user to add additional information to the results generated by the search engine, including production and broadcast date, sources and keywords for videos. It is also possible to rate the results. Finally, the user’s search itself is a source of information, providing data that is incorporated into the search engine; the metadata of a newly uploaded video, for instance, passes into the database.

“Comparing digital video data online or within video databases is very complex,” explains Christian Weigel from the Audio-Visual Systems research group at the IDMT. “Videos that share the same content have for the most part been edited, meaning that they are scaled and encoded in a variety of formats. Also, search engines are often unable to distinguish images cropped from a larger picture, lower thirds or the zoom shots so popular with US news channels.”

The demonstration version being presented at CeBIT will investigate how a selection of TV channels have made use of film footage, changed its form and broadcast it. The user interface displays commonalities and appraises them in graphic form. The search itself is conducted either by inputting text or by directly uploading individual video sequences. The researchers’ aim is to make the software sufficiently robust that it could also be used in the future to compare the multimedia content found on big online media portals. The scientists do not imagine archivists or journalists will be the only users. “NewsHistory is of particular interest to media and market researchers, say if they want to assess the televised political duels coming up this year,” concludes Weigel.

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Quantum computers could help search engines keep up with the Internet's growth

ScienceDaily (June 12, 2012) — Most people don't think twice about how Internet search engines work. You type in a word or phrase, hit enter, and poof -- a list of web pages pops up, organized by relevance.

Behind the scenes, a lot of math goes into figuring out exactly what qualifies as most relevant web page for your search. Google, for example, uses a page ranking algorithm that is rumored to be the largest numerical calculation carried out anywhere in the world. With the web constantly expanding, researchers at USC have proposed -- and demonstrated the feasibility -- of using quantum computers to speed up that process.

"This work is about trying to speed up the way we search on the web," said Daniel Lidar, corresponding author of a paper on the research that appeared in the journal Physical Review Letters on June 4.

As the Internet continues to grow, the time and resources needed to run the calculation -- which is done daily -- grow with it, Lidar said.

Lidar, who holds appointments at the USC Viterbi School of Engineering and the USC Dornsife College of Letters, Arts and Sciences, worked with colleagues Paolo Zanardi of USC Dornsife and first author Silvano Garnerone, formerly a postdoctoral researcher at USC and now of the University of Waterloo, to see whether quantum computing could be used to run the Google algorithm faster.

As opposed to traditional computer bits, which can encode distinctly either a one or a zero, quantum computers use quantum bits or "qubits," which can encode a one and a zero at the same time. This property, called superposition, some day will allow quantum computers to perform certain calculations much faster than traditional computers.

Currently, there isn't a quantum computer in the world anywhere near large enough to run Google's page ranking algorithm for the entire web. To simulate how a quantum computer might perform, the researchers generated models of the web that simulated a few thousand web pages.

The simulation showed that a quantum computer could, in principle, return the ranking of the most important pages in the web faster than traditional computers, and that this quantum speedup would improve the more pages needed to be ranked. Further, the researchers showed that to simply determine whether the web's page rankings should be updated, a quantum computer would be able to spit out a yes-or-no answer exponentially faster than a traditional computer.

This research was funded by number of sources, including the National Science Foundation, the NASA Ames Research Center, the Lockheed Martin Corporation University Research Initiative program, and a Google faculty research award to Lidar.

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The above story is reprinted from materials provided by University of Southern California.

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Journal Reference:

Silvano Garnerone, Paolo Zanardi, Daniel Lidar. Adiabatic Quantum Algorithm for Search Engine Ranking. Physical Review Letters, 2012; 108 (23) DOI: 10.1103/PhysRevLett.108.230506

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Quantum computers could help search engines keep up with the Internet's growth

ScienceDaily (June 12, 2012) — Most people don't think twice about how Internet search engines work. You type in a word or phrase, hit enter, and poof -- a list of web pages pops up, organized by relevance.

Behind the scenes, a lot of math goes into figuring out exactly what qualifies as most relevant web page for your search. Google, for example, uses a page ranking algorithm that is rumored to be the largest numerical calculation carried out anywhere in the world. With the web constantly expanding, researchers at USC have proposed -- and demonstrated the feasibility -- of using quantum computers to speed up that process.

"This work is about trying to speed up the way we search on the web," said Daniel Lidar, corresponding author of a paper on the research that appeared in the journal Physical Review Letters on June 4.

As the Internet continues to grow, the time and resources needed to run the calculation -- which is done daily -- grow with it, Lidar said.

Lidar, who holds appointments at the USC Viterbi School of Engineering and the USC Dornsife College of Letters, Arts and Sciences, worked with colleagues Paolo Zanardi of USC Dornsife and first author Silvano Garnerone, formerly a postdoctoral researcher at USC and now of the University of Waterloo, to see whether quantum computing could be used to run the Google algorithm faster.

As opposed to traditional computer bits, which can encode distinctly either a one or a zero, quantum computers use quantum bits or "qubits," which can encode a one and a zero at the same time. This property, called superposition, some day will allow quantum computers to perform certain calculations much faster than traditional computers.

Currently, there isn't a quantum computer in the world anywhere near large enough to run Google's page ranking algorithm for the entire web. To simulate how a quantum computer might perform, the researchers generated models of the web that simulated a few thousand web pages.

The simulation showed that a quantum computer could, in principle, return the ranking of the most important pages in the web faster than traditional computers, and that this quantum speedup would improve the more pages needed to be ranked. Further, the researchers showed that to simply determine whether the web's page rankings should be updated, a quantum computer would be able to spit out a yes-or-no answer exponentially faster than a traditional computer.

This research was funded by number of sources, including the National Science Foundation, the NASA Ames Research Center, the Lockheed Martin Corporation University Research Initiative program, and a Google faculty research award to Lidar.

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Story Source:

The above story is reprinted from materials provided by University of Southern California.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Journal Reference:

Silvano Garnerone, Paolo Zanardi, Daniel Lidar. Adiabatic Quantum Algorithm for Search Engine Ranking. Physical Review Letters, 2012; 108 (23) DOI: 10.1103/PhysRevLett.108.230506

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here