The good news about the Internet and its most visible component, the World Wide Web, is that there are hundreds of millions of pages available, waiting to present information on an amazing variety of topics. The bad news about the Internet is that there are hundreds of millions of pages available, most of them titled according to the whim of their author, almost all of them sitting on servers with cryptic names. When you need to know about a particular subject, how do you know which pages to read? It you’re like most people, you visit an Internet search engine.
Internet search engines are special sites on the Web that are designed to help people find information stored on other sites. There are differences in the ways various search engines work, but they all perform three basic tasks: They search the internet—or select pieces of the Internet—based on important words.
They deep an index of the words they find, and where they find them. They allow users to look for words or combinations of words found in that index. Early search engines held an index of a few hundred thousand pages and documents, and received maybe one or two thousand inquiries each day. Today, a top search engine will index hundreds of millions of pages, and respond to tens of millions of queries per day. In this article, we’ll tell you how these major tasks are performed, and how Internet search engines put the pieces together in order to let you find the information you need on the Web.
Looking at the Web Searches Per Day: Top 5 Engines Google- 250 million, Overture- 167 million, Inktomi- 80 million, LookSmart- 45 million, FindWhat- 33 million.
When most people talk about Internet search engines, they really mean World Wide Web search engines. Before the Web became the most visible part of the Internet, there ere already search engines in place to help people find information on the Net. Programs with names like “gopher” and “Archie” kept indexes of files stored on servers connected to the Internet, and dramatically reduced the amount of time required to find programs and documents. In the late 1980s, getting serious value from the Internet meant knowing how to use gopher, Archie, Veronica and the rest.
Today, most Internet users limit their searches to the Web, so we’ll limit this article to search engines that focus on the contents of Web pages.
An Itsy- Bitsy Beginning Before a search engine can tell you where a file or document is, it must be found. To find information on the hundreds of millions of Web pages that exist, a search engine employs special software robots, called spiders, to build lists of the words found on Web sites. When a spider is building its lists, the process is called Web crawling. (There are some disadvantages to calling part of the Internet the World Wide Web- a large set of arachnid-centric names for tools is one of them.) In order to build and maintain a useful list of words, a search engine’s spiders have to look at a lot of pages.
How does any spider start its travels over the Web?
The usual starting points are lists of heavily used servers and very popular pages. The spider will begin with a popular site, indexing the words on its pages and following every link found within the site. In this way, the spidering system quickly begins to travel, spreading out across the most widely used portions of the Web.
“Spiders” take a Web page’s content and create key search words that enable online users to find pages they’re looking for. Google began as an academic search engine. In the paper that describes how the system was built, Sergey Brin and Lawrence Page give an example of how quickly their spiders can work. They built their initial system to use multiple spiders, usually three at one time. Each spider could keep about 300 connections to Web pages open at a time. AT its peak performance, using four spiders, their system could crawl over 100 pages per second, generating around 600 kilobytes of data each second. Keeping everything running quickly meant building a system to feed necessary information to the spiders. The early Google system had a server dedicated to providing URLs to the spiders. Rather than depending on an Internet service provider for the domain name server (DNS) that translates a server’s name into an address, Google had its own DNS, in order to keep delays to a minimum.
When the Google spider looked at an HTML page, it took note of two things: The words within the page and where the words were found.
Words occurring in the title, subtitles, Meta tags and other positions of relative importance were noted for special consideration during a subsequent user search. The Google spider was built to index every significant word on a page, leaving out the articles “a”, “an” and “the”. Other spiders take different approaches.
These different approaches usually attempt to make the spider operate faster; allow users to search more efficiently or both. For example, some spiders will keep track of the words in the title, sub-headings and links, along with the 100 most frequently used words on the page and each word in the first 20 lines of text. Lycos is said to use this approach to spidering the Web.
Other system, such as AltaVista, go in the other direction, indexing every single word on a page, including “a”, “an”, “the” and other “insignificant” words. The push to completeness in this approach is matched by other systems in the attention given to the unseen portion of the Web page, the Meta tags.
The Problem with Keyword Searching
Keyword searches have a tough time distinguishing between words that are spelled the same way, but mean something different (i.e. hard cider, a hard stone, a hard exam, and the hard drive on your computer). This often results in hits that are completely irrelevant to your query. Some search engines also have trouble with so-called stemming—i.e. if you enter the word “big”, should they return a hit on the word, “bigger?” What about singular and plural words? What about verb tenses that differ from the word you entered by only an “s” or and “ed”?
Search engines also cannot return hits on keywords that mean the same, but are not actually entered in your query. A query on heart disease would not return a document that used the word “cardiac” instead of “heart”. Concept-based searching (This information is out-dated, but might have historical interest for researchers).
Excite used to be the best-known general-purpose search engine site on the Web that relies on concept-based searching. It is now effectively extinct. Unlike keyword search systems, concept-based search systems try to determine what you mean, not just what you say. In the best circumstances, a concept-based search returns hits on documents that are “about” the subject/theme you’re exploring, even if the words in the document don’t precisely match the words you enter into the query.
How did this method word?
There are various methods of building clustering systems, some of which are highly complex, relying on sophisticated linguistic and artificial intelligence theory that we won’t even attempt to go into here. Excite used to a numerical approach. Excites software determines meaning by calculating the frequency with which certain important words appear. When several words or phrases that are tagged to signal a particular concept appear close to each other in a text, the search engine concludes, by statistical analysis that the piece is “about” a certain subject.
For example, the word heart, when used in the medical/health context, would be likely to appear with such words as coronary, artery, lung, stroke, cholesterol, pump, blood, attack, and arteriosclerosis. If the word heart appears in a document with others words such as flowers, candy, love, passion and valentine, a very different context is established and a concept-oriented search engine returns hits on the subject of romance. This ends the outdated “concept-based” information section.
Refining Your Search
Most sites offer two different types of searches- “basic” and “refined”. In a “basic” search, you just enter a keyword without sifting through any pull down menus of additional options. Depending on the engine, though, “basic” searches can be quite complex. Search refining options differ from one search engine to another, but some of the possibilities include the ability to search on more than one word, to give more weight to one search term than you give to another, and to exclude words that might be likely to muddy the results. You might also be able to search on proper names, on phrases, and on words that are found within a certain proximity to other a certain proximity to other search terms.
Some search engines also allow you to specify what form you’d like your results to appear in, and whether you wish to restrict your search to certain fields on the internet (i.e. use net or the web) or to specific parts of web documents (i.e. the title or URL).
Many, but not all search engines allow you to use so-called Boolean operators to refine your search. These are the logical terms AND, OR, NOT, and the so-called proximal locators, NEAR and FOLLOWED BY.
Boolean AND means that all the terms you specify must appear in the documents, i.e. “heart” AND “attack”. You might use this if you wanted to exclude common hits that would be irrelevant to your query.
Boolean OR means that at least one of the terms you specify must appear in the specify must appear in the documents, i.e. bronchitis, acute OR chronic. You might use this if you didn’t want to rule out too much.
Boolean NOT means that at least one of the terms you specify must not appear in the documents. You might use this if you anticipated results that would be totally off-base, i.e. nirvana AND Buddhism, NOT Cobain.
Not quite Boolean + and – Some search engines use the characters + and – instead of Boolean operators to include and exclude terms.
NEAR means that the terms you enter should be within a certain number of words of each other.
FOLLOWED BY means that one term must directly follow the other.
ADJ, for adjacent, serves the same function. A search engine that will allow you to search on phrases uses, essentially, the same method (i.e. determining adjacency of keywords).
Phrases: The ability to query on phrases is very important in a search engine. Those that allow it usually require that you enclose the phrase in quotation marks, i.e. “space the final frontiers”.
Capitalization: This is essential for searching on proper names of people, companies or products. Unfortunately, many words in English are used both as proper and common nouns- Bill, bill, Gates, gates, Oracle, oracle, Lotus, lotus, Digital, digital- the list is endless.
All the search engines have different methods of refining queries. The best way to learn them is to read the help files on the search engine sites and practice!
Most of the search engines return results with confidence or relevancy rankings. In other words, they list the hits according to how closely they think the results match the query. However, these lists often leave users shaking their heads on confusion, since, to the user; the results often seem completely irrelevant.
Why does this happen?
Basically it’s because search engine technology has not yet reached the point where humans and computers understand each other well enough to communicate clearly.
Most search engines use search term frequency as a primary way of determining whether a document is relevant. If you’re researching diabetes and the word “diabetes” appears multiple times in a web document, it’s reasonable to assume that the document will contain useful information. Therefore, a document that repeats the word “diabetes” over and over is likely to turn up near the top of your list. If your keyword is a common one, or if it has multiple other meanings, you could end up with a lot of irrelevant hits. And if your keyword is a subject about which you desire information, you don’t need to see it repeated over and over—it’s the information about that word that you’re interested in, not the word itself.
Some search engines consider both the frequency and the positioning of keywords to determine relevancy, reasoning that if the keywords appear early in the document, or in the headers, this increases the likelihood that the document is on target. For example, one mehod is to rank hits according to how many times your keywords appear and in which fields they appear (i.e. in headers, titles or plain text). Another method is to determine which documents are most frequently linked to other documents on the web. The reasoning here is that if other folks consider certain pages important, you should, too.
If you use the advanced query form on AltaVista, you can assign relevance weights to your query terms before conducting a search. Although this takes some practice, it essentially allows you to have a stronger say in what results you will get back.
As far as the user is concerned, relevancy ranking is critical, and becomes more so as the sheer volume of information on the web grows. Most of us don’t have the time to sift through scores of hits to determine which hyperlinks we should actually explore. The more clearly relevant the results are, the more we’re likely to value the search engine.
Information on Meta Tags
Some search engines are now indexing web documents by the Meta tags in the documents’ HTML (at the beginning of the document in the so-called “head” tag). What this means is that the web page author can have some influence over which keywords are used to index the document, and even in the description of the document that appears when it comes up as a search engine hit.
This is obviously very important if you are trying to draw people to your website based on how your site ranks in search engines hit lists.
There is no perfect way to ensure that you’ll receive a high ranking. Even if you do get a great ranking, there’s no assurance that you’ll keep it for long. For example, at one period a page from the Spider’s Apprentice was the number-one-ranked result on AltaVista for the phrase “how search engines word”. A few months later, however, it had dropped lower in the listings. There is a lot of conflicting information out there on meta-tagging. If you’re confused it may be because different search engines look at meta tags in different ways. Some rely heavily on meta tags, others don’t use them at all. The general opinion seems to be that meta tags are less useful than they were a few years ago, largely because of the high rate of spamdexing (web authors using false and misleading keywords in the meta tags). It seems to be generally agreed that the “title” and the “description” meta tags are important to write effectively, since several major search engines use them in their indices. Use relevant keywords in your title, and vary the titles on the different pages that make up your website, in order to target as many keywords as possible. As for the “description” meta tag, some search engines will use it as their short summary of your URL, so make sure your description is one that will entice surfers to your site.
In the keyword tag, list a few synonyms for keywords, or foreign translations of keywords (if you anticipate traffic from foreign surfers). Make sure the keywords refer to, or are directly related to, the subject or material on the page. Do NOT use false or misleading keywords in an attempt to gain a higher ranking for your pages. The “keyword” meta tag has been abused by some webmasters. For example, a recent ploy has been to put such words “sex” or “mp3” into keyword meta tags, in hopes of luring searchers to one’s website by using popular keywords.
The search engines are aware of such deceptive tactics, and have devised various methods to circumvent them, so be careful. Use keywords that are appropriate to your subject, and make sure they appear in the top paragraphs of actual text on your webpage. Many search engine algorithms score the words that appear towards the top of your document more highly than the words that appear towards the bottom. Words that appear in HTML header tags (H1, H2, H3, H4, H5, H6) are also given more weight by some search engines. It sometimes helps to give your page a file name that makes use of one of your prime keywords, and to include keywords in the “alt” image tags.
One thing you should not do is use some other company’s trademarks in your meta tags. Some website owners have been sued for trademark violations because they’ve used other company names in the meta tags. I have, in fact, testified as an expert witness in such cases. You do not want the expense of being sued!
Remember that all the major search engines have slightly different policies. If you’re designing a website and meta-tagging your documents, we recommend that you take the time to check out what the major search engines say in their help files about how they each use meta tags. You might want to optimize your meta tags for the search engines you believe are sending the most traffic to your site.