I have decided to make a concerted effort via reminders and automated pokes to keep my blog updated more often. To jumpstart that effort i have decided to post a short speech that i wrote for a speaking class back in 2000. The speech was about search. At the time, search was widely on a pay-per-ranking model and google was the only real relevant search engine. Nobody had really heard of google at this time as it had very little market share, was pre-ipo and was generally not widely used.
I could see the need for relevancy in search even at that time. The speech might seem a little dated but the piece that is not dated are the statistics on the growth of knowledge in general. This exponential growth also applies to knowledge bits in the enterprise whether they be documents, blog posts, IM threads or just enterprise facts stuck in the head of a knowledge worker.
We can manage these types of knowledge in their own taxonomies that are best suited for each type but in the end the power to search for these, either by full text relavancy, tag clouds or other types of search, is what makes them of value to the enterprise. Ok enough of an introduction here is the speech in full. Remember it was given way back yonder in 2000. :)
The sum total of humankind's knowledge doubled from 1750-1900. It doubled again from 1900-1950. Again from 1960-1965. It has been estimated that the sum total of humankind's knowledge has doubled at least once every 5 years since then. It has been further projected that by the year 2020, knowledge will double every 73 days. This statement was made by Patricia Breinik in her book Student Learning in the Information Age. As the information available on the internet increases exponentially over time, so will the value of search and particularly search engines. Learning how to search for answers is important for all of us, whether we do it as students, workers, parents or just for the love of knowledge. I have literally spent years trying out different search engines and watching them evolve since the inception of the internet as we know it today. Our discussion on search engines will center around the types of search engines as represented by their business models, the one type of search engine that has proved to be a search engine in the purest sense and a look at a successful business model of this search type. But first, what types of search engines are there?
Well, search engines can be classified into two major categories or types of searches. These categories are the paid search rank and the relevant search rank. The paid search rank is where advertisers pay to be seen at the top of a search query. The company that pays the most for the position will receive the number one ranking and so will have a better chance of having someone click through to their site. This serves the purpose of generating cash flow for the company who owns the search engine as well as for those that pay to have their websites ranked high on a search query result as they will receive greater traffic than they could generate on their own. Many portals or (definition here) started off with this business model and eventually became hubs of links know as portals such as yahoo, excite and alta vista all of whom are now portals giving users a massive starting point of links based on various subjects.
The second type of search is the relevance search. This is a search that bases its results on the relevancy of a pages answer to your query. (quote from cnet news.com here) With this method, pages are ranked according to the relevance to words, content and links to other sites. A voting method is employed in which a web page or site receive points when other sites link to it. Those other pages are voting that the page they are linking to has value. An example of the difference between the two types of engines is the query of "Canada". Entered at a paid search site you would receive the first five pages filled with travel agency links promising the best airfare prices to Canada. Enter your search term of Canada at a site that judges relevance and the first return would be Canada.gov, the official site of Canada the country. Can you see the difference?
Well, what types of engines are out there that employ relevance as a search model? One of the most comprehensive relevant search engines is Google.com. They invented and patented their own brand of relevant searching called PageRank which was described earlier. Google conducts 150 million searches a day for users. The google search engine is an index of over 2 billion web pages and is updated constantly. The search engine that indexes the next larges number only indexes 7% of the number of pages that Google does. The engine is available in 35 languages and is so good at language translation that if there is a relevant site to your search in another language or country, you can choose to have the page translated for you on the fly. Google is profitable, debt free and privately held, a testament to its business model of paid keyword adds that are viewable down the side of the page but do not count towards page ranking.
As we have seen, the value of search cannot be underrated. Considering the types of search engines and the business models behind them can help us make the right choice. The value of search comes down to relevance. Do you want to be sold a product or are you after the results that best match your search query? Search is the filtering of knowledge...and knowledge is power. Ask yourself this question. When the sum total of humankinds knowledge doubles every 73 days, will you have the power to harness it?
