חיפוש רעיון בגוגל

הדעה הרווחת היא שהחיפוש בגוגל הוא גם מהיר וגם מעולה

נדמה לרגע שיש לבינה המלאכותית סיכוי טוב להצליח

אבל כשמחפשים בגוגל אחרי מילה 

שיש לה משמעויות שונות המחשב מתבלבל 

ובמקום להביא מלון במובן של בית הארחה 

הוא מביא תמונה של פרי 

רמת הקושי עולה כשמחפשים בגוגל אחרי רעיון 

כי ניתן ניתן להביע רעיון במחרוזות מילים שאין ביניהן שום דמיון כמו:

הכל הבל 

או הכל דיבורים

או אין משמעות

או מילים מילים 

או כלאם פאדי 

או גנבת דעת

אז אחרי שאתה מחפש מלון ומקבל מה שלא ביקשת

גוגל מציעה לך לתקן את החיפוש ל"מלון פרי"

אבל כשאתה מחפש רעיון ומקבל תוצאות לא רצויות

ולא מקבל את התוצאות הרצויות

אפילו אם אתה משנה שוב ושוב את מילות החיפוש 

אתה מבין את גודל המרחק שבין מה שהבינה המלאכותית מספקת

לבין מה שאנחנו מקווים ממנה לספק

Copyrights and Free Resources For Building A Web Site

In order to build a successful web site you need to get a lot of relevant texts and a lot of relevant photos. You need huge amounts of texts to rank high on Search Engine Results Pages but without photos texts tend to get boring. A successful web site aims at prolonging visitor’s stay, using seducing tactics like the colors the flowers use to prolong the staying of the bees…
One can write his own texts and publish his own photos, but it will take him much longer than being helped also by others’ texts and photos. Others’ texts and photos are copyrighted. So the question is where on the WWW are free resources for building successful web sites?
1. Fair Use: text is free up to about 300 words as long as you reference the quoted source.
2. Wikipedia is an excellent resource without any limits on the length of the quote.
3. Books and newspapers, which don’t have valid copyrights anymore. E.g. Gutenberg project’s thousands of on line books.
4. Creative-Commons photos. E.g. Flickr, Jewish Encyclopedia.
5. Getting permission to publish texts and photos from copyrights holders.

Readers are encouraged to add free resources on the comments section of this web page.

Axioma Search Engine

My neighbor sent me this link to an article in Hebrew about Axioma and I hurried to download it and to try it out. My first impression is that it is fun and that the team there did a good job. Investor Arie Adler can be satisfied from the result...

On their web site I read that Axioma

Allows you to interactively increase the relevancy and context searches you make on general search engines… You arrive at more relevant results quickly - without weeding through a lot of unwanted results.

So the idea behind Axioma is to solve the problem of relevancy, the problem of “lot of unwanted results”- but can they do that?

IMHO Axioma will never solve the problem of relevancy because it is built on the wrong concept: it is a macro content search engine, which means that even if you get the web-page you wanted you still have to find your way in it, and what if you need only one small paragraph from a page that contains hundreds of irrelevant paragraphs? And what if the data you need is scattered in 10 different results? – you’ll have to enter each result separately, just like you did in the “old" search engines that the “new” Axioma is destined to save us from.

Only micro content strategy will help essentially solve this problem. QTSaver is a step in that direction. Axioma is a step in the opposite direction…

Searching problems with Google Images

Searching images for my research about the Star of David is very frustrating. The captions of the best images I found so far had no relevant keywords like:
Star of David
Shield od David
Davids's shield
Magen David
Solomon's Seal etc.
I found them by scanning hundreds of photos that answer search words like
Roman Mosaics Sicily
Bardo Museum Tunisia, etc.
This problem seems unsolvable...

Another problem I stumbled upon was that my own photos from Flickr didn't publish on Google Images and I wandered why. I asked around and nobody knew. Today I noticed that my traffic meter shows visitors to my site who were referred to it by Google Images. I searched on Google Images for "star of David" Flickr and got 248 answers - a few dozens of them were mine. So the answer is that it takes six months until Google Images adds new photos to its pool.

Tagging Pictures is Bad Hunting

Searching pictures in any search engine is very clumsy and inaccurate. It depends totally on the description of the picture or on its tags (in case it is tagged on a photo sharing on line software like Flickr). The tags (or descriptions) are focused on the interests of the tagger, which don't always match the needs of the other WWW users.

E.g. I'm interested in Stars of David. There are dozens of pictures in Flickr which are tagged Menorah but include Stars of David. There are other items on these pictures which are not retrievable since the only thing that interested the tagger was the Menorah. Let's say that there are ten interesting items on each picture - imagine how much information is lost only because we (WWW users) don't tag properly.

This problem doesn't exist on text search. All the text "items" are retrievable.

I am quite skeptical about finding possible solutions for this problem, but I believe the more we use micro content anthologies the easier it will be to retrieve these "lost sheep". For example, I hope that in my micro content project people will find pictures that deal with Stars of David and were not tagged by the relevant tags in the place where I found them. The same goes for other websites that collect everything there is to know about a certain subject.

How to Reach the Top in MSN SERP

My subject matter is Stars of David. On the left side of this article you'll see a link to My MICRO CONTENT PROJECT and that's the place where I deal with it. There is a tough competition in this field – in Google there are 197,000,000 results for the query Star of David. Anyhow this morning my blog reached the first place on MSN SERP out of 10,467,906 results containing the words Star of David.

I want to tell you how I did it because I have a certain vision behind it:
1. Four months ago I opened a blog on Blogger. Blogs get priority on certain search engines and IMHO it's better to start a blog than to start a web site.
2. I entered my target keywords into my domain name – I heard that this may help promoting your site. [http://star-of-david.blogspot.com/]
3. Each Day I posted about three times– regular updating wins points for you on certain search engines.
4. I found all the content I needed on the WWW and edited it so that each posting was interesting, concise, and short. I added many photos (Creative-Commons and photos I shot) to prevent problems with copyrights. These two steps ensured that the reader will feel that he is treated respectfully and doesn't waste his time.

It took me four months, seven hours a day, and about 300 postings to reach the first placement on MSN SERP, but now I believe I (and each one of you) can repeat this achievement with any other subject matter. You can calculate the expenses easily. If you hire a student for four months, seven hours a day, his salary is what it costs to be first in your field in MSN. When I'll reach the first place in Google or Yahoo I'll try to calculate how much this will cost…

Any how the point is that finding content on the WWW is an obstacle. Snippets were misleading and I spent most of my time on opening irrelevant links and closing them. I believe QTSaver can save 75% of this lost time because it helps choose the right articles. It also helps a lot by suggesting words for further research. This means that the cost for placing whatever you want on the first link of MSN SERP will cost you only one month salary and to me it sounds like an excellent bargain.

The result is that people who are interested in Stars of David get answers on a totally different level of relevance than they are used to. Imagine what will happen when millions of sites will become collections of micro contents on a special subject. It will change the WWW from Chaos to a friendly neighborhood. That's my vision. This is what I'm working on. Search Engine Optimizers that will understand the economic benefits of this vision will make it happen. Not because they believe in a better visual reality, but because this is the shortest and cheapest way to get to the top.

Right now QTSaver is not ready for this kind of operation since it retrieves only from the first dozens of results, but it is quite simple to change the algorithm so that QTSaver will work on all the SERP. Now I need an investor to make this happen. -Any volunteers?

Google Book Search Beta

Today I entered the search words "Shield of David" into http://books.google.com/ and got 1020 answers. I read 130 snippets, chose to open 20 links, and found after all this trouble 4 lines I needed and 2 pages that were "interesting" for further research. This was much less than I expected.

Conclusions:
o The bottom line - it was a waste of time. I could find more new data on a regular search engine
o This method of research brought me macro contents that included more paragraphs than I needed
o Snippets were misleading - promised good info but after opening the link they were not what I expected
o Most of the pages weren't relevant or their contents were already known to me
o 2-3 pages were technically in bad print quality and I couldn't read them
o Some interesting beginnings didn't allow me to see the next page
o I couldn't copy and paste

Maybe it is a good search engine for those who want to know which books are in their field of interest, or for getting introductory material, but for getting more info about something I already knew about it was disappointing!

Micro Content Project

In the last three months I was posting to my new blog about the star-of-david. This is an online Micro Content Project which can be a model for any research. I want to find everything I can about my subject (Star of David in my case);
1. I get thousands of results for my queries.
2. I enter each result and copy what I need to a new document.
3. The first five results are great!
4. After the first 50 results things are repeating themselves and I get lost.

The snippets under each link of the search engines are misleading. They promise a relevant micro content and find an irrelevant one, or a duplicate of what I already found. It takes hours to find a new item after the first 100 results.

Qtsaver can solve this problem if we build a new version that will give RELEVANT snippets for thousands of results; but we need an investor to make this happen…

Ori Alon Made It

In the last year I wrote a lot about QTsaver's competitor, Ori Alon. The news is that Google acquired his text search algorithm. Google confirmed that "Ori Alon works at Google's Mountain View, California offices." Alon's Orion search engine was developed for getting the most relevant textual results.

Now it is hard for me to estimate whether Google "killed" Orion or whether they are going to develop it. I also have no clue about the consequences this acquisition will have on the future of QTSaver which is competing in the same field of relevant textual results.

Anyhow – I congratulate you, Ori Alon. It must be great for you to be acknowledged by the best search engine in the world, better than getting a gold medal.

MicroContent Local Search

The more words you put into the search engine's query window the less results you get.  Local search reduces search results- it is like adding a name of a place to every query. Actually you can make a local search on any general search engine by adding a name of the place to your original search words – like: Madonna + New York.

 

But local search engines not only save entering names of places - they collect not only pages that mention the name of the desired place but also pages that belong to the place without mentioning it, like webpages belonging to certain businesses that are situated in the desired place. Local search engines may even identify users' location and retrieve results which are relevant to it.

 

Search localization is a new phenomenon and it is developed  simultaneously by all the mane players in the search engines arena: Google, Yahoo!/Overture, AOL and MSN, and by others.

 

Local searches have one big disadvantage – they are MACRO CONTENTS, which means that if the page talks one time about the place you want and 100 times about other places you'll have to ignore the irrelevant paragraphs in order to find the one you love. This can be really exhausting when you want to collect information from several Websites.

 

I believe QTSaver can be a great  improvement to local search engines, because it collects only the relevant paragraphs. Today QTSaver runs only on the first top results but my dream is that in the future it will run on all the millions of search results and collect all the relevant paragraphs to a separate database. Such a system will have the chance to be called a perfect  local search engine.

 

 

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Dream Search Engine

Yesterday I asked on Yahoo-Answers:

How would a dream-search-engine look like?

For example: one answer instead of zillion results

-Relevant results instead of irrelevant ones etc.

 

I got eight answers:

Five answerers thought that it would look like Google.

One  thought that it would look like MSN.

 

Utcursch wrote:

 

It won't "look" like anything. You just think of what to search for, and the results would be front of you, in the format you want them. That would be the dream-search-engine.

Giveu2tictacs wrote:

 

design one that learns your search style. Example: If I seach for items like clothing, vases, tables. Then the search engine will learn that I am most likely shopping and put primary result for stores first rather than an article about vases. It could also understand that the user always makes the same typing errors. So I type in vaces instead of vases. The search engine would see the spelling error and bring up results for the word I implied.

 

I chose the last answer as the Best Answer, but I think that for the time being the question was more impressive than the answers.

 

 

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Answering Yahoo Answers Beta with QTSaver

I think some of the questions on Yahoo Answers Beta can be answered on the fly by using QTSaver. Answerers who will use QTSaver will discover that they get a lot of points for giving the best answers. I am going to try to answer as many questions as I can just to test the possibilities of this new system .

 

For example:

On http://answers.yahoo.com/question/index;_ylt=Ah8bb3bB7mELIgT80Gs4EOrzy6IX?qid=1006031400488

 

Cyberbob asked:

 

1. How can i keep myslf frm getting distracted by thoughts while i am studying?

 

I entered the words: distracted thoughts studying into QTSaver and in one minute copied three relevant links and pasted them for Cyberbob's:

 

http://www.innerconscious.com/may2k2.htm... The Inner Conscious
http://www.csu.edu.au/division/studserv/... Student Services - Charles Sturt University
http://www.adprima.com/studytips.htm... Study Tips from Students

Source(s): www.qtsaver.com

 

Now I'm waiting anxiously to see if I get the desired 10 points for the best answer.

 

 

 

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Anna Benson

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Findory

While preparing my posting about Personalized Search I stumbled upon Findory as one of the heralds of the new Personalized Search era. The bottom line is that Findory tries to save users' time by giving them more relevant results, but most of the time each result contains relevant information mixed with irrelevant information and the users are still wasting their time. So what's the big deal?

Other than that on most popular search engines a query about QTSaver brings some results – on Findory none. What did I do? I submitted my Blog to Findory`. I got a message saying that "It might take a few happy seconds. Patience is a virtue". Then I waited and waited but nothing happened. Let's hope that in a few days I'll search for my postings and find them on Findory…

Here are some relevant excerpts I collected after entering one query about Findory to QTSaver:

 

http://www.techcrunch.com/?p=199

September 3, 2005 Company: Findory Launched: January 2004 Location: Seattle, WA

Findory, which is almost two years old, is a pioneer in this area and has a unique solution. Findory is a personalized newspaper that evolves, quickly, as you click and read. Greg and his co-founder Alex Edelman, spent years at Amazon prior to creating Findory, and gathered extensive experience in recommending new products to Amazon users. They have three silos of information, all personalized - news, blogs and search. Findory looks at your historical clickstream and presents only related information. It evolves real-time as you search, browse, click and read stuff that interests you

 

http://en.wikipedia.org/wiki/Findory

Findory is a personalized news site, started by Greg Linden that aggregates thousands of news sources. It learns from the articles users click on to build a personalized news page for each user.  Findory appears to use a collaborative filtering algorithm to recommend interesting news items. A notable feature of Findory is that it does not require users to register or to explicitly rate items. Instead, it uses an anonymous cookie and personalizes using your reading history.

 

http://en.wikipedia.org/wiki/List_of_news_aggregators

Findory is a personalized news and weblog reader. It learns from the articles you read, searches thousands of sources, and helps you discover news you would otherwise miss.

 

http://glinden.blogspot.com

Top Stories from My Favorites is a personalized selection of articles picked from your favorite feeds. It's designed to emphasize interesting articles based on your reading habits rather than forcing you to read every single post from every single blog in your feed reader.  Findory Favorites now allows you to read up to 200 stories, 20 at a time. I added a feature called Findory Tags that automatically extracts common keywords used by a news source or weblog.

 

http://www.programmableweb.com/api/Findory

Our API enables developers to retrieve Findory news and blog article data by making parameterized URL requests over HTTP (otherwise known as REST). The results are returned in RSS format for your convenience

 

http://www.techcrunch.com/2005/09/25/findory-adds-self-evolving-feed-reader

Findory has built up a loyal following in the nearly two years since its launch. However, many users requested the ability to include RSS feeds of their choice directly into their blog and news channels. Greg and Alex just added this functionality, making Findory nearly perfect as a news source and reader.

Findory users now have the ability to add feeds directly into Findory - one at a time, via an OPML cut-and-paste or simply by directly importing your feeds from Bloglines, if that is your current reader.

Once you’ve imported these feeds, the powerful Findory personalization engine takes over and presents posts to you in a personalized way, based on what you (and community members like you) tend to find interesting.

Findory is squarely attacking the current efforts by Attensa, SearchFox, Personal Bee and others to present your feed information in a more intelligent and useful way. The standard readers quite simply don’t work for power users with 100+ feeds any more - and companies are trying very hard to find ways of sorting through this information for you before you start to read. And unlike Attensa (who hasn’t launched their personalization product yet) and SearchFox (in private beta, although you can get an invite fairly easily), Findory is live and open to everyone.

 

http://dondodge.typepad.com/the_next_big_thing/2006/02/findory_persona.html

Greg Linden is founder of Findory, and author of the popular blog "Geeking with Greg". Findory is a personalization and recommendation service that helps users find news stories and blog posts of interest to you. Findory also has a search engine built in that personalizes its results based on your past searches and clicks. Think Memeorandum combined with Google personalized search, powered by a collaborative filtering engine.

Findory is primarily a recommendation engine.

 Personalization learns what you want from what you do. Using personalization, Findory helps focus your attention and surface things that you may not have been able to find on your own.

 Findory is quite a bit different. Unlike Digg or Jookster, there is no explicit voting or listing friends. Findory's personalization learns from what you do, finds other people with similar interests to yours, and shares what they have found, all implicitly, all anonymously, all without any effort. Unlike Memeorandum, Wink, and Digg, every reader sees a different page on Findory, each page personalized to each person's interests.

When you read articles on Findory, Findory looks for other readers who might have the same interests as you, and then shares the articles they found. It is a little like social networking sites where you explicitly list all your friends, then explicitly share things you found among your friends. But, with Findory, friends are found for you automatically and anonymously. With Findory, the sharing is done quietly and implicitly, all with no effort.Just read articles, that's it. Findory does all the work for you.

 The personalization techniques used by Findory fall loosely into the class of collaborative filtering algorithms. However, naive collaborative filtering has well known quality, performance, and scaling problems. Findory creates fully personalized pages in real-time, works even if someone has read only a few articles, learns immediately from new data, and can scale to millions of users.

 To my knowledge, there are no other start-ups doing personalized information like Findory. However, the search giants have made tentative efforts toward personalization. Google has an experiment with "recommended stories" on a small section of the Google News page and also has an active effort in personalized web search.

 

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Personalized Search

Personalized Search is considered to be one of the main steps in the evolution of search engines, but it is meant to retrieve MACRO CONTENTS, which means that even when you'll get the  most satisfying result for your query you may still get a lot of irrelevant information that will capture your attention and waste your time. QTSaver already minimizes this risk but imagine how it would be like to get Personalized Search microcontents from 20 documents on the same page!

Here are some excerpts I collected for those of you who want to have deeper knowledge of this issue.

 

http://www.webpronews.com/news/ebusinessnews/wpn-45-20040803IsPersonalizedSearchtheFuture.html

 Personalized Search is viewed as one of the directions search may head in the future, as Search Engine Watch's Danny Sullivan pointed out at the Search Engine Strategies San Jose conference.  ChoiceStream CTO Michael Strickman pointed out that Personalized Search means different things to different people. By his definition personalization is any method that uses understanding of the user to provide better results.  He's found that consumers do have quite an interest in Personalized Search but they need more information before they'll be willing to participate.  A good example of Personalized Search, he said, is A9, which keeps track of searches and is able to retrieve the information to allow people to repeat those same searches at a later time.  Google is working on its own subject-based form of Personalized Search, where the user sets up a profile and search results can be filtered to the user's area of interest.  One form of personalization, attribute-based Personalized Search, uses an understanding of page content to improve the search results the user sees. ChoiceStream analyzes and scores pages by their attributes, looking for categories, the type of page (ex: product review sites, blogs, etc.), and the style.  Another problem is that many people don't want to reveal too much information…This seems to be a huge barrier to the success of Personalized Search.  There are also risks to Personalized Search, Michael said, including the risk of actually making the search results worse, rather than more relevant to the user. To be successful, the users' interests should also be the top priority and should always remain in control of what's considered relevant. Attributes must be chosen correctly, should reflect user interest, and also cut across many search categories.

 

http://www.imediaconnection.com/content/4977.asp

 Personalized Search January 27, 2005 by Steve Johnson

 The real gains in terms of search relevance and, importantly, search-related revenue are on the horizon now with the advent of "Personalized Search. "Recently, there's been a lot of attention placed on Personalized Search with announcements from Yahoo!, Google, Eurekster, MSN and Amazon. So, what exactly is Personalized Search and how can it be used to drive revenue?

 Personalized Search is the fine-tuning of search results and advertising based on an individual?s preferences, demographic information and other factors. Presumably, the better a search engine understands a user's interests and preferences, the better able it is to target search results, advertising, sponsored links, etc.

 For example, suppose a user searches for information to help him plan a vacation to Aruba. Without Personalized Search, the user receives thousands of content links and ads based purely on their global relevance -- i.e., how relevant they are to consumers in general -- without regard for this individual consumer's lifestyle and interests. With Personalized Search, the results take on an entirely new level of relevance. Results returned to a budget-conscious traveler vacationing with his wife and children are different from those returned to, for example, a more upscale traveler who vacations with friends. These personalized results are first filtered according to a search engine's basic criteria, such as popularity, keyword relevance, etc., and then they are automatically tuned to meet the individual's specific needs.  It is easy to see how consumers benefit from this new technology: They receive targeted search results, ads, sponsored links and more that are tuned to their particular needs and interests. What is less obvious is the benefit of Personalized Search to agencies, advertisers and site marketers.

 The reality is that Personalized Search drives financial benefit to all of these constituencies -- both in the short term and long term. In the short term, advertisers increase revenue by targeting ads and promotions at the users who are most likely to click and buy. In the example above, advertisers could target value-oriented hotels, flights and other promotions to the budget traveler while offering an entirely different set of ads to upscale, sophisticated consumers.

 Studies show that consumers want personalization and are more willing to stay with sites and services that know them and respond to their specific lifestyles and preferences. Sites that employ Personalized Search automatically filter the Web for consumers based on their individual preferences. This saves consumers time and frustration, and bonds users to the site.

 

http://glinden.blogspot.com/2005/04/google-launches-search-history.html

 Like Findory and A9 but unlike Yahoo and Ask, Google's search history feature is integrated into the main search on the site. Keeping search and clickthrough history is a first step toward Personalized Search. The next big step is to use this data to reorder search results, making the results more relevant to your particular interests and needs.

 In his article on Google's new search history feature, Chris Sherman says: Don't expect Yahoo, Ask Jeeves, MSN or AOL Search to stand still. Personalized Search has long been touted as one of the holy grails for the industry ...Beginning today with Google's launch of My Search History, I expect to see major leaps ahead in the arena of Personalized Search -- and that's a good thing. None of the search giants personalize search results yet. But, little guys like good old Findory have taken some early first steps, changing web search results in a limited way based on search and clickthrough history.

 Being first only helps if you push that advantage. A9 has gone in a few other interesting directions -- local search with photos and distributed search with OpenSearch -- but they haven't delivered anything new in Personalized Search for a year. Now it's looking like Google and Yahoo are positioned to lead in Personalized Search.

 

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Claria RelevancyRank

Every now and then I hear about a new competitor that has a new recipe to beat Google Yahoo, and MSN. Checking the new claim I discover another macro content search engine that ignores the built in problems that macro contents homonyms and synonyms pose to every computer search program. After reading the following excerpts I draw from QTSaver I think you'll agree with me that chances that Claria  RelevancyRank will beat Google on the macro content play ground are low.

 

http://www.traffick.com/2005/08/behavioral-analysis-is- Claria -building.asp

 Claria 's RelevancyRank, a search technology under development, challenges Google, Yahoo, and MSN with a comparison of where they would rank the sites that RelevancyRank (based on behavioral indicators that  Claria  gathers by following users around with its adware) would rank in the top ten for the phrase "cheap tickets." The demonstration shows that MSN, Yahoo, and Google don't rank a lot of highly relevant sites (as far as Claria and its advertisers are concerned) in the top ten. For those scoring at home, Yahoo "won" on the sample query, by a score of 50 to 40 (Google) to 18 (MSN). Not too surprising given the strong business relationship between Yahoo and Claria! Maybe the "failure" of search engines to rank behaviorally-compelling sites as high as Claria does isn't the point, though. On one hand, site quality can definitely be measured by some recipe of indicators based on fuller analytics, such as time spent on site, etc. On the other, certain metrics (such as commerce-related ones) might not be the best ranking criteria.

 

http://www. Claria .com/companyinfo/press/releases/pr050713.html

REDWOOD CITY, CA - July 13, 2005

Claria SM (www. Claria .com), a pioneer and leader in the behavioral marketing space, today announced the alpha release of Claria's Vista Marketing Services search platform. Leveraging its RelevancyRankTM (www.relevancyrank.com) behavioral search technology, the new search platform goes far beyond analyzing links to pages and hypertext matching, and instead evaluates how consumers actually interact with search results when they are seeking information on the Web.

In January 2004, Claria began development of its patent-pending RelevancyRank technology. RelevancyRank is a revolutionary search capability that ranks Web pages based on consumer surfing behavior. The technology incorporates basic metrics such as click rates, as well as critical post-click metrics of consumer behavior - such as time spent viewing a site, number of pages viewed at a site, number of return visits to a destination Web site, historical interests based on Web-wide surfing habits, and conversion behavior. While in the past Claria utilized RelevancyRank technology solely to benchmark and evaluate other search engine results, this alpha release marks the first time this technology has been incorporated into a search engine platform.

 

 

http://www.webrankinfo.com/english/seo-news/topic-2183.htm

Here are 3 sites about Claria Debuts RelevancyRank: Search Ranking By Behaviorial Activity:

Claria - Company Information - News RoomClaria Debuts RelevancyRank: Search Ranking By Behaviorial Activity SearchEngineWatch, March 2005 "Claria, the company behind the eWallet software, ...http://www.claria.com/companyinfo/press/articles/2005.html

 

 

The Search Engine Report - Number 101Claria Debuts RelevancyRank: Search Ranking By Behavioral Activity SEW Blog, Mar. 15, 2005.

Summaries of Search Engine News As It Happens - Search BrainsClaria Debuts RelevancyRank: Search Ranking By Behavioral Activity Source: Search Engine Watch Blog URL: http://Blog.searchenginewatch.com/Blog/050315-...http://www.searchbrains.com/5532.html

 

http://www.prnewswire.com/cgi-bin/stories.pl?ACCT=104&STORY=/www/story/03-15-2005/0003196233&EDATE

The study indicated that while there is considerable room for improvement among the top search engines in terms of providing relevant results, Yahoo! performed better than MSN and Google, providing search results Internet users ultimately found valuable more often. The study was conducted using the Claria Corporation's patent-pending RelevancyRank(TM) technology (http://www.relevancyrank.com) which identifies the most relevant search results based on millions of Internet users' actual behavior.

  By using a full view of searchers' behavioral data, RelevancyRank technology provides the truest measure of relevance for online search. RelevancyRank represents an additional use of the behavioral insights technology platform offering from Claria's Vista Marketing Services division. The division launched the BehaviorLink advertising network in February 2005. "We are driving the next generation of search technology where relevancy is driven by what millions of people find meaningful," stated Jeff McFadden,  Claria  CEO.

 "RelevancyRank is part of a suite of personalized Web technologies Vista Marketing Services will be unveiling in the coming quarters that further personalize the consumer's Web experience."

 

http://sev.prnewswire.com/advertising/20050713/SFW05313072005-1.html

 REDWOOD CITY, Calif., July 13 /PRNewswire/

 In an initial study developed in conjunction with Harris Interactive, RelevancyRank search technology proved to be equal or better than Google and Yahoo! search results over 85 percent of the time in terms of both satisfaction and relevancy.

 Google recently announced that it is publicly testing a new service that uses search histories of individuals to influence what search results they see. RelevancyRank technology goes significantly further as it could incorporate both consumers' search history and Web surfing behavior, resulting in a more relevant and customized experience.

 

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