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September 11, 2008

18 U.S., 3 International Systems Added to Google Transit

Whether you live in or visit cities with transit systems, it's always good to know when and where the buses and trains are running. Google has been teaming up with transit systems across the country and around the world. Today, they're announcing the addition of 18 U.S. transit systems and 3 international city systems to Google Transit.

United States

MetroLink Transit (Los Angeles, CA metropolitan region)
Irvine Shuttle (Irvine, CA)
OMNITRANS (San Bernardino County, CA)
Roseville Transit (Roseville, CA)
AC Transit (Alameda & Contra Costa County, CA)
Broward County Transit (Broward County, FL)
Miami-Dade Transit (Miami-Dade County, FL)
Metropolitan Atlanta Rapid Transit Authority (Atlanta, GA)
Metro Transit (Minneapolis, MN)
Mountain Line (Missoula, MT)
Capital District Transportation Authority (Albany, NY)
Greater Cleveland Regional Transit Authority (Cleveland, OH)
Central Ohio Transit Authority (Columbus, OH)
Cleveland Area Rapid Transit (Norman, OK)
Island Transit (Island County, WA)
Jefferson Transit Authority, (Port Townsend, WA)
Green Bay Metro Transit (Green Bay, WI)
Mountain Line Transit Authority (Morgantown, WV)

International

Ottawa in Canada
Olsztyn, Poland
Moscow, Russia

Posted by Nathania Johnson at 8:43 AM | Permalink | Comments (1)

June 5, 2007

Google Adds Transit Data to Maps

Google has been showing locations of train, bus or subway stops on its maps, but now those locations will link directly to more detailed information about a specific station, route, or schedule, according to the Google LatLong blog. An example shows data for the NYC subway at 59th St - Columbus Circle Station, New York.

Transit info is gathered from a city's transit agency, geographic data companies, or other sources. A city transit organization can submit their data to Google for inclusion via a text file feed.

Posted by Kevin Newcomb at 12:34 PM | Permalink

October 4, 2006

New Search Patent Filings: October 4, 2006 - Using Google to find the Cable Guy

A few new patent filings from Microsoft, Google, and Amazon.com. Microsoft explores the use of self organizing maps in one patent filing, and shows how those could be used to make geographic searches more relevant. They also explore URL canonicalization in another.

Google's newest patent filing expands upon Google Transit and Maps by providing information about taxi cabs, shuttles, limos, delivery trucks, moving vans, and other service vehicles.

Amazon is granted a patent for recommendation services.

Microsoft

This first patent application discusses the use of self organizing maps to increase search relevancy. It points to Self Organization of a Massive Document Collection as a reference source for readers of the patent filing, to help them understand how such a process could be implemented.

System and method for improving search relevance Invented by Christopher Weare Assigned to Microsoft US Patent Application 20060218138 Published September 28, 2006 Filed on March 25, 2005

Abstract

A system and method for performing context based document searching is provided. A grid of content tiles is constructed corresponding to a desired concept space. Each content tile is assigned a content tag and is associated with a series of feature values. The feature values are trained to correspond to various regions of the content space. Documents are associated with one or more content tags based on a comparison of document feature values with content tile feature values. A search query is modified to include one or more content tags based on the terms in the search query and/or user preferences. The search query is then matched to documents associated with content tags contained in the search query.

The ideas in the previous document from Microsoft could be used to help increase the value of some specialized searches, such as ones based upon geographical location information. This next patent application is a companion filing to that one, and relies upon the same technology to help with searches where location is important.

System and method for location based search Invented by Christopher Weare, Ashley Feniello, and Randy Kern Assigned to Microsoft US Patent Application 20060218114 Published September 28, 2006 Filed: March 25, 2005

Abstract

A system and method for performing geographic based document searching. A grid of location tiles is constructed corresponding to a desired geographic area. A location tag is assigned to each location tile. Documents are searched to identify a geographic location. The documents are associated with one or more location tags based on the location tiles corresponding to the identified geographic location. The geographic location of a search query is also identified. The search query is modified to include one or more location tags corresponding to the location of the search query. The search query is then matched to documents associated with location tags contained in the search query.

Not long ago, three researchers from Technion, including Google's Ziv Bar-Yossef, published a paper called Do not Crawl in the DUST: Different URLs with Similar Text. The following patent filing from Microsoft's Marc Najork visits some of the same territory, looking carefully at ways to pick the best single URL for pages that are substantially similar yet are at different URLs.

Systems and methods for inferring uniform resource locator (URL) normalization rules Invented by Marc Alexander Najork Assigned to Microsoft US Patent Application 20060218143 Published September 28, 2006 Filed: March 25, 2005

Abstract

Different URLs that actually reference the same web page or other web resource are detected and that information is used to only download one instance of a web page or web resource from a web site. All web pages or web resources downloaded from a web server are compared to identify which are substantially identical. Once identical web pages or web resources with different URLs are found, the different URLs are then analyzed to identify what portions of the URL are essential for identifying a particular web page or web resource, and what portions are irrelevant. Once this has been done for each set of substantially identical web pages or web resources (also referred to as an “equivalence class” herein), these per-equivalence-class rules are generalized to trans-equivalence-class rules. There are two rule-learning steps: step (1), where it is learned for each equivalence class what portions of the URLs in that class are relevant for selecting the page and what portions are not; and step (2), where the per-equivalence-class rules constructed during step (1) are generalized to rules that cover many equivalence classes. Once a rule is determined, it is applied to the class of web pages or web resources to identify errors. If there are no errors, the rule is activated and is then used by the web crawler for future crawling to avoid the download of duplicative web pages or web resources.

Google

Google has been adding cities to its transit service, provides information about traffic congestion in some areas, and has supplied driving directions for quite some time. Can they expand their services to help us hail a taxi, find out how close the Fedex truck when delivery a package, and let us know where the cable guy we are waiting for is?

User location driven identification of service vehicles Invented by Mark Crady, Michael J. Chu and Russell Y. Shoji US Patent Application 20060217885 Published September 28, 2006 Filed: March 24, 2005

Abstract

A vehicle position aggregation system receives position information for service vehicles from various fleet management systems, and maintains the current location of the vehicles in a database, including information identifying each vehicle's associated fleet and related contact information. End users can query the vehicle position aggregation system to obtain information about service vehicles in the vicinity of the user's input location.

Amazon.com

There have been a few patent filings from Amazon on recommendation systems. This one looks at similarities between items to make recommendations.

Personalized recommendations of items represented within a database Invented by Jennifer A. Jacobi, Eric A. Benson, and Gregory D. Linden Assigned to Amazon.com US Patent 7,113,917 Granted September 26, 2006 Filed: May 7, 2001

Abstract

A computer-implemented service recommends items to a user based on items previously selected by the user, such as items previously purchased, viewed, or placed in an electronic shopping cart by the user. The items may, for example, be products represented within a database of an online merchant. In one embodiment, the service generates the recommendations using a previously generated table that maps items to respective lists of "similar" items. To generate the table, historical data indicative of users' affinities for particular items is processed periodically to identify correlations between item interests of users (e.g., items A and B are similar because a large portion of those who selected A also selected B). Personal recommendations are generated by accessing the table to identify items similar to those selected by the user. In one embodiment, items are recommended based on the current contents of a user's shopping cart.

My usual reminder about patents: Some of the processes and technology described in patents are created in house, and some are developed with the assistance of contractors and partners. A percentage are never developed in a tangible manner, but may serve as a way to attempt to exclude others from using the technology, or even to possibly mislead competitors into exploring an area that they might not have an interest in (sometimes skepticism is good.)

There are times when a Google or Yahoo acquires a company to gain access to the intellectual property of that company, or the intellectual prowess and expertise of that company's employees. And sometimes patents are just purchased.

Want to comment or discuss? Visit our Search Technology & Relevancy area of the Search Engine Watch Forums.

Posted by Bill Slawski at 6:11 PM | Permalink

December 8, 2005

Google Labs Quietly Releases Transit Trip Travel Planner for Portland, Oregon

Via Yahoo's Zawodny: Word of Google Transit Trip Planner. This new Google Labs beta (not to be confused with Google Ride Finder, that's one we haven't heard about in a while) allows people in Portland, Oregon (ONLY) (sorry, Portland, Maine) to "plan trips [with Google Maps] using public transportation." Sort of a Google mashup of its own. Unfortunately, when I tried several examples, they all came back saying, "Sorry, we were unable to calculate transit directions between xxx and xxx." Well, that's a Google beta for you. (-;

Are more cities coming soon? The FAQ puts it this way, "Sorry, but we don't yet have any definite plans for which cities will be added and when." However, public transportation officials from other cities are invited to contact Google.

Although I was unable to get it to work I can see from the FAQ that the Trip Planner also provides you with an estimate of how much it would cost to drive instead of using public transit.

Are transportation services the next big area for big G? Let's see, Google Ride Finder in March, links to air travel fare and timetable info last month, the lonog time availability of airline flight tracking, and now this. Could Google use its computing power to build reservation and other needed info systems?

Btw, if you're looking to check out another cool transportation tool, only available for select cities including San Francisco, check out NextBus.com. It's even available for Portland's streetcar. It offers real time info as to when the next bus, train, streetcar, or other form of transportation will be arriving at a specific location. Come to think of it, I could see this company ripe for either a partnership with a large search company or even a buyout. More info here.

Posctript: Google has registered the domains: GoogleTransitplanner.com., .info.,.org. and .net and GoogleTripPlanner.net, .org, and .info In case you're wondering, GoogleTripPlanner.com was registered to a person in Virginia last month. Thank to G.R. for his help with this one.

Posted by Gary Price at 2:55 AM | Permalink

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