Overview of the travel search engine market

Travel remains the single largest component of e-commerce according to Forrester Research, a consulting firm in Cambridge, Mass.  But despite the dominance of such online travel agency heavyweights as Expedia.com, Hotwire.com, Orbitz.com, Priceline.com and Travelocity.com, most users consult multiple Web sites when shopping online for travel The average consumer visits 3.6 sites when shopping for an airline ticket online, according to PhoCusWright, a Sherman, CT-based travel technology firm. Yahoo claims 76% of all online travel purchases are preceded by some sort of search function, according to Malcolmson, director of product development for Yahoo Webkatalogeintrag PR6 Travel.The 2004 Travel Consumer Survey published Jupiter Research noted that "nearly two in five online travel consumers say they believe that no one site has the lowest rates or fares." Thus a niche was created fo aggregate travel search such as Kayak.com, Lowfares.com, Dohop.com or Trabber.com which seek to find the lowest rates from multiple travel sites, obviating the need for consumers to cross-shop from site to site.  Even in emerging markets such as China and India, Qunar.com and Ixigo.com have adopted this model with considerable success.  Within the class of travel search engines are several subcategories of sites that offer a range of services and search methods:

Portal sites

Several of the leading generic search and information aggregator sites also offer travel components.  In the broadest sense, virtually any search engine could be considered a travel search engine.  However, some generic search engines also should be ranked as TSEs, since they include both paid and unpaid links to travel sites and maintain "travel" pages, often accompanied by original editorial content.  This category of generic search sites includes About.com, AOL, MSN, and Yahoo.Webkatalogeintrag PR6

Aggregate sites

These sites use technological tools generate an aggregate result from other travel sites, including third-party travel agency sites such as Expedia.com, Orbitz.com , and Travelocity.com, and branded sites maintained by individual travel companies, such as  Delta.com, Hilton.com, or Hertz.com, for example.

Consolidators and bargain sites

These sites collect and publish bargain rates by advising consumers where to find them online (sometimes but not always through a direct link).  Rather than providing detailed   search tools, these sites generally focus on  offering advertised specials, such as last-minute sales from travel suppliers eager to deplete unused inventory; therefore, these sites often work best for consumers who are flexible about destinations and other key itinerary components.  This category includes sites such as Cheapflights.com, Travelzoo.com, Kayak.com, TripSchedule.com, and USAToday.com’s travel listings.

See also

Google: Scaling with the Web

Creating a search engine which scales even to today's web presents many challenges.  Fast crawling technology is needed to gather the web documents and keep them up to date. Storage space must be used efficiently to store indices and, optionally, the documents themselves. The indexing system must process hundreds of gigabytes of data efficiently. Webkatalogeintrag PR6 Queries must be handled quickly, at a rate of hundreds to thousands per second.

These tasks are becoming increasingly difficult as the Web grows.  However, hardware performance and cost have improved dramatically to partially offset the difficulty. There are, however, several notable exceptions to this progress such as disk seek time and operating system robustness.  In designing Google, we have considered both the rate of growth of the Web and technological changes.  Google is designed to scale well to extremely large data sets. It makes efficient use of storage space to store the index.  Its data structures are optimized for fast and efficient access (see section 4.2).   Further, we expect that the cost to index and store text or HTML will eventually decline relative to the amount that will be available (see Appendix B). This will result in favorable scaling properties for centralized systems like Google.

Design Goals

Improved Search Quality

Our main goal is to improve the quality of web search engines. In 1994, some people believed that a complete search index would make it possible to find anything easily.   According to Best of the Web 1994 -- Navigators,    "The best navigation service should make it easy to find almost anything on the Web (once all the data is entered)."   However, the Web of 1997 is quite different. Anyone who has used a search engine recently, can readily testify that the completeness of the index is not the only factor in the quality of search results.  "Junk results" often wash out any results that a user is interested in. In fact, as of November 1997, only one of the top four commercial search engines finds itself (returns its own search page in response to its name in the top ten results).Webkatalogeintrag PR6 One of the main causes of this problem is that the number of documents in the indices has been increasing by many orders of magnitude, but the user's ability to look at documents has not.  People are still only willing to look at the first few tens of results. Because of this, as the collection size grows, we need tools that have very high precision (number of relevant documents returned, say in the top tens of results).  Indeed, we want our notion of "relevant" to  only include the very best documents since there may be tens of thousands of slightly relevant documents. This very high precision is important even at the expense of recall (the total number of relevant documents the system is able to return).  There is quite a bit of recent optimism that the use of more hypertextual information can help improve search and other applications [Marchiori 97] [Spertus 97] [Weiss 96] [Kleinberg 98]. In particular, link structure [Page 98] and link text provide a lot of information for making relevance judgments and quality filtering.  Google makes use of both link structure and anchor text (see Sections 2.1 and 2.2).

Academic Search Engine Research

Aside from tremendous growth, the Web has also become increasingly commercial over time.  In 1993, 1.5% of web servers were on .com domains. This number grew to over 60% in 1997. At the same time, search engines have migrated from the academic domain to the commercial.  Up until now most search engine development has gone on at companies with little publication of technical details.  This causes search engine technology to remain largely a black art and to be advertising oriented (see Appendix A).  With Google, we have a strong goal to push more development and understanding into the academic realm.

 Another important design goal was to build systems that reasonable numbers of people can actually use.  Usage was important to us because we think some of the most interesting research will involve leveraging the vast amount of usage data that is available from modern web systems.  For example, there are many tens of millions of searches performed every day.  However, it is very difficult to get this data, mainly because it is considered commercially valuable.


Webkatalogeintrag PR6