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Dan: Welcome to the Full Circle Resource Kit Podcast.

Our topic today is operators and how we use them to build our search queries and I'm very pleased to have with me Chris Sherman. Chris, for some our listeners who may not be familiar with your background and work, just tell us a little bit about yourself.

Chris: Sure, I'm the Executive Editor of searchengineland.com. That's a relatively new web site that is focused on watching what is going on in the world of web search - interpreting it, reporting it, and offering people advice - both for searching the web, but also for search marketers who are interested in improving their rankings or getting visibility on the search engines.

Prior to that I was Executive Editor of searchenginewatch.com which is a site that has been around for more than 10 years now. It's one of the first sites that actually started observing search engines. [I] was involved pretty heavily in the Search Engine Strategies conferences and moving forward, in partnership with Danny Sullivan, who I worked with at searchenginewatch.com, we're going to be organizing a series of in-person conferences and webinars all covering search.

Dan: Wonderful. Well, you certainly are someone who has been watching and working directly in this area of search for a number of years and our Resource Kits are really designed to synthesize and bring some of those insights to the educators who are working with the children and the young people in the schools so that they can become effective searchers. So, I'm gonna ask you a practical question here: How critical are operators in refining a search query?

Chris: Well, the whole question of operators is a really good one, because there are two kinds. One are the more traditional Boolean operators and what's tricky about those is that the search engines don't implement them in the same way that more formal systems like Dialogue or LexusNexus or even some library databases implement them. They are loosely defined by the search engines and they don't always work the way that you think they would work.

A particular example of that is the OR operator. It's partially because human beings don't think of the word "or" in the same way that search engines do. If you take an example - say you go out to breakfast and you order and the waitress asks, "Do you want your eggs scrambled or fried? Do you want coffee or tea? Do you want toast or a biscuit?" In each case what you are doing is eliminating one choice, in other words excluding one of the options so that you get a really nice breakfast. Now a search engine by contrast treats "or" as "either/or", in other words, including both options. So you can imagine the mess that you would get if you ordered breakfast from a search engine. It wouldn't be what you really expected at all. So, I kind of call that whole thing, "To OR is human" because we really do think of it very differently than a machine.

My advice basically is, if you are going to use Boolean operators, with each of the search engines get in and really read what it is that they are doing and how to use the operators. Otherwise you are probably going to be disappointed. In fact, you may end up wasting time.

Dan: My question is, if I am looking at Google or Yahoo or MSN, are each of those going to be using the OR operator in a different way or is there some consistency there?

Chris:  No. They are all different and in some cases it is dramatically different and in some cases it is subtly different. It often depends actually on what you are searching for.

Dan: And as you mentioned, if we look at proprietary databases or library databases, those might be using the OR operator, or other operators differently as well.

Chris: They are and in fact they implement true Boolean logic when you use them. So with those systems you can use the Boolean operators with a lot more confidence.

Dan: Of course, you have to have good key words as well. That seems to be another piece of this puzzle.

Chris: That's right.

Dan:  So what developments do you see coming in search engines and how is that going to impact how students and users build their queries?

Chris: Well you know it is interesting that you mention the importance of good key words. I absolutely agree - if you don't have the right words it's going to be a lot harder to find what you are looking for. So what we have been seeing over the past year - or a little bit longer actually - are all of the search engines now suggesting related searches. You can see this in Google down at the bottom of many search result pages, you can see it at Yahoo at the top of the search result page.

Interestingly, I think the search engine that does this the best is Ask.com because on the right side of the search result pages at Ask they don't even have sponsored listings - the paid advertisements that Google, Microsoft and Yahoo have. Instead, they have very, very powerful refinement tools. They have suggested links to narrow your search. They have links to broaden your search.

And I think one of the most interesting is they have - it's hard even to explain what it is - but it's conceptually-related links. So if you are searching for a name - say you are looking for information about one of the Beatles - maybe John Lennon or Paul McCartney. You will see in Ask's search list results a list of related names - Ringo Starr, George Harrison and so on. So that can really, really help you uncover potentially things you wouldn't have thought about or even things that are unknown to you. It's a good learning tool to find out what the search engine thinks is actually related to what it is that you are searching for.

Dan:  So that sounds like it is really looking at synonyms or is it not?

Chris: It's synonyms but in Ask's case it even goes beyond that. It's really looking for more conceptual relationships between the search terms.

Dan: So as long as the folks who are designing the algorithms are picking words that truly are related it can be a very powerful tool. But then you are kind of abdicating part of your search keywords to somebody else who has chosen, "well these are the ones that are conceptually related."

Chris: That's right. But remember the search engines have years and years of experience in interacting with their users and basically watching as users will pick and choose what they think are good results. And so they have accumulated that experience and basically distilled it into their algorithms, their procedures for finding results. So they are going on a lot of experience and a lot of very smart people who are doing the programming and so on. And I would argue that because they do have that experience behind them, unless you are a really, really good, very experienced searcher, you're better off in most cases trusting the judgment of the search engine rather than trying to do something on your own.

Dan: Well, that's a great point. One question that we'll wrap up with that I have had often asked to me is, "What about Ask Jeeves?"

Chris: Well, Ask Jeeves is actually Ask.com, the search engine I was just talking about. They actually did a complete makeover. They fired the butler, no age discrimination lawsuit yet. And basically they really focused on becoming a core search engine. Interestingly they've dropped the whole part of natural language - ask a question, get an answer. But they've also really refined their natural language capability and they do in fact support that kind of questioning.

You can go in and ask a question in English. Quite often what you'll end up finding is that Ask will end up giving you what they call a Smart Answer. So if you ask a question like, "Who is Leonardo da Vinci?" At the very top of the page before you even see web search results or some of these related suggestions, you'll see perhaps a picture of Leonardo da Vinci, a short two or three sentence biography, maybe a link to a Wikipedia entry, or some other reference site - lots of different information that they call Smart Answers. It's trying to basically, almost short-circuit or bypass the web search process so that you don't have to go out and hunt through the different search results. But in fact, you get a very short list of links that leads you very directly to very, very reliable reference sources. So I think they are doing an extremely good job.

Dan: Are they though teaching something that would be a little counter-intuitive where, when we go into Google or Yahoo - these other search engines - we are saying, "Don't use natural language questions because there is a lot of noise in there. It's not going to look for all of the stop words anyway. When they go to Ask, students are more likely to put in their full natural language question but then that's not really as transferable a skill when they are going back into the other search engines. So what do we do with that tension?

Chris: Well, you know Ask has really downplayed the whole natural language thing. So they are not really pushing that. What they are doing is really supporting it underneath the interface itself. That said, I think all the major search engines over the next 5 years or so are really going to improve dramatically their natural language capabilities.

Dan: Well, excellent. It's been just really great talking with you Chris and you've brought a wealth of insight and information to our discussion on operators and I just want to thank you for taking the time to be with us today.

Chris: Sure, Dan. It was a pleasure.

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Dan:  This is a production of the 21st Century Information Fluency Project at the Illinois Math and Science Academy.