Archive for the 'information seeking' Category

Search isn’t king anymore: Google recognises browsing

Earlier this week, I was doing some Googling and I noticed something weird: Google now has facets that are visible all the time:

Google search results showing a range of left-hand facets and an updated interface, for example a new button shape.

Google with facets

You might also notice that the interface appears more modern–the shape and appearance of the button has changed, for example.  You can read more about that at the Google blog, but it’s notable that a lot of what they have done is good for users; the new logo is more readable and will likely be faster to download for example.

The thing that really excites me is that Google has recognised that search is no longer king: by including always-visible facets on the Google results page, they have recognised that browsing, refining, and manipulating results sets are part of the natural human information seeking process.

Larry Page (one of Google’s founders) once said that “the ultimate search engine would…always give you the right thing. And we’re a long….way from that”. I don’t think he’s right, and the reason why I don’t think he’s right is that it is not always readily apparent, even to the information seeker themselves, what they want. Sometimes, it’s easy to figure out what information will answer our questions; when we want to know what the formula is to convert degrees fahrenheit to degrees celsius, for example, information seeking in the information age is straightforward and requires only a simple search ( ‘how to convert from deg c to deg f‘will get a perfectly serviceable answer, and in fact if all you want to do is convert a temperature you can use Google’s ‘in’ operator by typing ‘16 C in F‘, for example).  Sometimes, though, you don’t know exactly what you want; “a good present for my brother” or “a good book” or “how users search the library shelves” are information needs that can’t be met by typing a simple phrase into Google; they require a process that includes searching, browsing, and refining.  Take the “good book” example from above; you might feel like a mystery or modern literature, and once you;ve decided on that you might like a certain author or subgenre, but who or what that might be might also require some digging around to discover, and once youv’e decided what you want to read you have to figure out how to get it–as an ebook? from a library? from a bookstore, either online or physical? This example shows how we search out there in the real world when there isn’t a straight answer (and sometimes not even a straigth question), and how important it is to have the option to browse; again taking the book example, browsing might also show you other books that seem like you might enjoy them.

This isn’t the first time I’ve talked about Google and browsing–I’ve discussed before what a great thing it is that Google is incorporating browsing (and you can read more about how important browsing is in that post), and how their choice of facet location has influenced where we put the facets in our library search (and I’m really glad we went with Google on this one now). This is the most exciting time I’ve talked about it, though; Google’s results pages now reflect a truly natural information seeking process (without destroying the interface for “quick searches”), and thus represent a much better user experience than they have in the past.  Not only that, but this development will have a feedback effect: because Google has them, facets are more likely to be used in other information seeking interfaces (because users are used to them), and thus the experience of many of these interfaces will be improved as well.


Google search isn’t just search anymore

I know I’m a bit lot late to the table with this, but Google search isn’t restricted to just searching anymore!  They’ve introduced some browsing tools as well (see the video below for more):

Now, it’s easy to figure out that I am very pro-browsing, and therefore I think it’s great that Google has included these things into their search experience, but I’d like to unpack just why I think browsing is such a good thing (and make a couple of suggestions for extensions of what Google is doing) along the way.

Google has been very pro-search as an information organisation and finding strategy for a long time, their search-don’t-sort appraoch to gmail being one obvious example of this.  It’s completely understandable that this has been Google’s whole approach for so long, after all, search is what they do (and they do it very well).

Search isn’t always the answer though (and if you watch this video of a Google user experience researcher talking about the search options, it is evident that Google knows that).  For one things, humans employ more than just search in their information seeking strategies: the research (PDF) shows that information seeking is generally an interative process that includes searching, browsing, and refinement.  Not only is search not the only approach we use for finding information, but sometimes search isn’t enough on its own: with all the information on the web, it can be hard to know when someone types ‘Placebo’ into a search box whether they want to know about the psychological effects of sugar pills, or whether they’re interested in the British based rock band (this ambiguity applies to any number of terms). Similarly, information seekers may want a particular type of information (for example reviews, or places where a product can be bought), or information from a particular geographic location, time or author, or general subject field.  Also, even with known-item searches (those where the searcher knows exactly what they are looking for, and that it exists somewhere, because they have found a pointer to it or seen it) if the searcher doesn’t remember the exact words that occur in the document, they might not find what they are looking for.

Google’s ‘more search options’ are beginning to deal with this problem.  They allow people to find three specific types of content (reviews, forums and video), they provide suggested search terms, they allow the user to look at results from a specific time, and also see how the search terms popularity has changed over time.  I’m not entirely sure what value the ‘wonder wheel (see below)’ adds, given that the related search terms provide all the wonder wheel terms and more, but  I suppose some people may find the visual presentation useful.

Google's wonder wheel, a visual display of related search termsIt certainly is heartening, for someone as vested in browsing as I am, to see Google incorporating browsing into their search.  All I want now is to see it expanded:  I want to filter news by topic and country (and standard search results for that matter); when I use Scholar, I want to be able to browse by author or year.  What Google has provided is an excellent start, and I look forward to seeing where this goes in the future.

One of these things is not like the others: Livingsocial’s recommender services

Last year I did an experiment: I logged every book I read, complete with tags about timing, subject matter, fiction or non-, andf themes, in Google books.  This was inherently satisfying to my curiosity (63 books last year, 24 of whiuch were non fiction), but was lacking something I’m interested in: a recommendation feature.

During the year, I discovered I could also log my books in Facebook, in a service that does have a recommender feature based on ratings (but no tags, sadly–I know, I should have just used librarything in the first damn place).  Thus I entered the exciting world of LivingSocial, which accepts ratings for books, albums, movies…and restaurants.

While I haven’t bothered too much with the music recommender service (though I should try, since my taste is all over the place), but I have found the book service and the movie service to be quite exciting–I’ve seen lots of books and movies I want to read/see.  So when I noticed last night that they also had a restaurant section, I was cautiously excited: I love food and I am always looking for places to try, but I suspected that it might be a US-only service.  It’s not, but I still wouldn’t recommend it to anyone, mostly because it doesn’t take into account the differences between books/movies/albums and restaurants:

  • Availability of large, relatively comprehensive catalogues: There are a wide range of relatively-comprehensive online catalogues for books and movies–think Amazon or LibraryThing. The same is not true for restaurants: there may be listings in the local yellow pages for some towns, some of which may be available online, but these listings would be difficult to harvest and far from comprehensive.  As a response to this, Livcingsocial will actually allow you to add your own restaurant listings, but only after you have rated 20 restaurants.  If you don’t do a lot of travelling, and your city doesn’t have any restaurants listed, this could be a bit difficult.
  • Location dependence: Subject to availability, playing equipment and local censorship laws, books/movies/albums may be enjoyed anywhere.  Restaurants, however, are only really available to those living or travelling (let’s be generous) within say 100 km (60 mi) of the restaurant’s physical location.
  • Amount of information required to make a decision: Everyone has certain requirements of their entertainment, for example:  some people find swearing offensive, some people dislike science fiction intensely, some people cannot abide restaurants that won’t take bookings, some people are vegetarian.  Recommendations for books/movies/music are more likely to meet people’s requirements (going back to our example those who dislike science fiction will universally rate it lower, thus feeding each other’s recommendations) and even if they don’t, it is much easier to find out ahead of time that they are bad (in the example of swearing parental advisory stickers are a good clue). In the case of restaurants, however, there are more paramters in play (food, service, noise level, ambiance, wheelchair accessibility, child-frioendliness, diaetary requirements) and this type of thing is harder to tease out in a five point rating, and often harder to discover before making the time investment to actually go to the restaurant.

The restaurant recommender is based on the same principles as the other recommenders, the amazon style “people who liked x also liked y, and you like x so you will probably like y”.  My experience with it, however, was quite frustrating: I rated a significant number of restaurants (not without some difficulty, as there aren’t that may listed in Melbourne, so I had to go to other cities I had lived in), and then clicked on “recommendations”.  Most of the recommendations were for restaurants in the US, and there was no way to generate recommendations for a a specified geographic region.  If I were travelling to the US any time soon, this might be helpful if I were going to the specific cities where restaurants were recommended for me, but generally speaking, these recommendations are useless.

The problem here is that a model that works well for small physical items has been applied to experiences, and it simply doesn’t work–making the user experience clunky and ultimately frustrating, possibly more often than it is helpful.  LivignSocial would have been better to stick with wine!

Have you ever tried a product or service from a company that did other things well only to be disappointed?

Human meaning in machine encoding? Thoughts on the semantic web

Tim Berners-Lee, the inventor of the world wide web, outlines his goals for the semantic web in the book he wrote about the development of the web.  I love his dream, that one day we would be able to ask “find out where a baseball game was played today and it was also 22C”.  I just don’t believe it is very likely to happen, for two reasons:

  • Effort
  • Natural language

The effort question is a really interesting one.  Somewhere along the line, someone has to expend the effort to make human semantic concepts in some way machine encoded, or, alternatively to answer their own questions.  For some, a certain level of machine encoding of the semantics they personally attach to an object (usually in the form of tags) is useful, either for some purpose of their own (information retrieval, for example), or for some social-capital reason (see a more detailed explanation of this here).  However, when a person has only a small amount of information to organise they are considerably less likely to add semantic information to it.

If there is no human being willing to expend the effort to add semantic information, there may be a human being willing to write computer programs to extract such information.  This will be more or less successful dependent on the kind of information to be extracted, and what it is to be extracted from, for example:

This is lesser effort than tagging, because it can be done once and used multiple times, but it is still effort that someone has to expend.

One further approach is, as in this paper (sorry, paywall), leveraging human-created tags to allow machines to do things that look like they understand the semantic web–so in the paper, for example, the author wrote a program that used the way people had combined tags on flickr to unsdersdtand what concrete things (for example tulips) were associated with abstract concepts (for example spring).

In any of the three cases human effort is required to generate the information needed for machines to do the kind of processing Berners-Lee suggests the semantic web ought to be able to do for us.  To actually get people to expend this effort requires them to have a special interest in it, either at a personal level (as with tagging) or a research interest (as with automatic extraction programs.  I think this effort is a major impediment to more widespread “semantic web” applications and uses.

The natural language question is also a barrier, and a much more usability centred barrier.  Even if we could get evertyhing tagged up, either by human hands or automatically, how people would then ask this semantic web to answer their questions is an open question.  glenn, an acquaintance of mine who works in the field (and like his name spelt wiht a lower case ‘g’) thinks that we need query languages, and I am inclined to agree.  If natural language searching on the free-text internet fails (paywall again, sorry), it will surely fail in any kind of structured environment.  Unfortunately, users are known to do poorly with Boolean search, and it is reasonable to expect that other query languages would porduce similarly bad results, so even if the web was tagged up, it may still be fairly difficult for the average user to ask the question Berners-Lee posed in his book.

I think tagging is great, because it imbues objects with personal meaning, and allows people to find things more easily.  I have yet to see evidence of a truly workable (and by implication usable) semantic web, though, and as such I don’t believe people will be able to answer questions about baseball games at 22C for some time to come. I also believe that even when it is possible to answer these soorts of questions, it will be not because of advanced tagging of web-pages, but more form advanced text processing by search engines–and that isn’t the semantic web, it’s search engine companies prioritising user experience.



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