All roads lead to search (and advertising)

Though my beginning is this field was with search, in recent years, I have not focused on it. Expect that to change, as we increasingly focus on search with SlideShare. A huge part of what we are doing is to webify the content locked up in powerpoint and other presentation files. Webifying the content means enabling it to be found by anyone who might be interested. It means search. We realize that our search sucked (there is no other way to describe it) and we did not want users to wait while we fixed it. So, the first step was simply to outsource the problem to Google – meaning use their custom site search. However, this is simply a starting point. We expect to come back and build other types of advanced search more suited to the specific nature and format of the content on SlideShare.

The second issue I am increasingly interested in is Advertising. As you can imagine, that is something we are playing around with on SlideShare. We want to get more experimental – trying more formats and placements – both with Google ads (which we currently have and on our own) and on our own.

So readers, what blogs should I start reading as I pursue this interest? Are there any books/articles that are a must read?

BayCHI Social Search panel – Podcast is online!

Last week we had a great BayCHI panel on Social and Personalized Search. Participants were from Netflix, Live365,, Pandora and digg. I moderated it. The podcast for that panel is now online. In inviting this particular group of panelists, I was hoping to highlight the changing trends in Social and Personalized Search. The companies were founded between 1997 – 2005 and their different approaches tells its own story. More about that inside.

For a more detailed desciption of the panel, go to Rick Boardman’s blog.

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Interesting talk by Google research scientist “Improving search by divining intent”

Terry Winograd runs an excellent seminar focused on HCI (at Stanford). I just saw from the mailing list announcement that this Friday (March 10th), the speaker is from Google. Dan Russell who used to be at IBM, is now a research scientist focused on the area of “search quality and user experience” at Google. He will talk about divining searcher intention. In recent months, Yahoo has made a series of high profile hirings of HCI researchers (Marc Davis comes to mind). I had not realized Google was making similar hirings. (I might be wrong here – please correct me if I am).

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Why Google wants to get closer to you (and why it bothers me more than Yahoo or Amazon’s personalization efforts)

Notice how much personalization Google has been putting out recently:
Personalized Search, the new release of the Toolbar has personalization, Google News now has recommended stories

Its clear why Google is doing this. Personalization is the next stage in the evolution of many products. It helps develop a closer relationship with users and get to know more about them. And most importantly, it provides a clear reason for Google to collect data and link it one individual. People do not want their web searches to be logged – partly because it does not provide any value for them. But we are fine with Amazon knowing a lot about us because there is a direct benefit in Amazon having our history. Google now wants the same type of relationship with you – its dear user. There are many business reasons for Google to pursue personalization.

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The blooming of information architecture at Google: A close look at facets, tags & categories in GoogleBase

I just spent some time with GoogleBase and was amazed at just how deeply Google has embraced standard information architecture concepts and trends. We have categories, facets, tags. I kid you not. Google of the simple search box with a go button has come a long way indeed.

A few top level categories

12 top-level categories (e.g., course schedules, Events & Activities) show up when you post a piece of content. Interestingly they do not get exposed directly in the search interface, but get used indirectly. Google uses your initial query to place you in a particular category, and show the relevant facets. For example, the facets presented when you search for a vehicle name are different than when you search for a recipe. This is a good approach, but it does mean that Google needs to guess the right category to present the appropriate set of facets. Google Product Manager explains that “Google Base suggests attributes and item types based on popularity, which you can use to define and attach your own labels and attributes to each data item.” So there is some magic going on behind the scene to decide what sets of facets to show.

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Google Blog search: Its a good start

A friend just sent me a link to Google Blog Search, and I spent some time looking at it. My first reaction: its about time that Google added in Blog Search. They have been building product after product, and ignoring something that is their core competency.

In the meantime, too many results from blogs often made web search difficult to wade through. There are two search situations – sometimes I want to search the web, find the most relevant item from results all over the web. At such times, I don’t want blog results – what some blogger said, just because its recent.

At other times, I want to find recent conversation about the topic. It should be relevant, but recency is more important. At such times, I want blog results.

In neither case could Google get me what I wanted – for a web search, the results were too influenced by blogs and recency. For a blog search, it was not sensitive enough to recency.

Which is why its great that at last Google has introduced “Blog Search“.

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The new blog tracking tool: Memeorandum

Memeorandum, launched today offers blog tracking by topics. Currently, it only covers tech and politics blogs. You can read more about the service at the blog of the creator Gabe RIvera here, or read a review by Robert Scoble here.

The screenshot below shows its coverage of the eBay-skype story.


Gabe says that the goal is to recognize the web as editor: “… there are rather large communities of knowledgeable, sophisticated commentators, … signaling in real time what’s worthy of wider discussion. I want memeorandum to tap this signal.”

Also, he talks about “relating the conversation”. “Communication on the web naturally tends toward conversation”, and Gabe wanted to make sure that Memeorandum recognized this conversation.

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Technorati – please take a page from Google’s design

I was just looking up something on Technorati and realized just how distracting I find the cute visual design – especially, the images to the left the search bar. Every time I go to that page, I find that my eyes go to those cartoonish figures. They are cute, but I am there to find something, not for the cute visual design.

aug13_technorati_google.gif And what’s with such a busy page? Seems like every possible option (Technorati Blog, Get Indexed, Personalize, Tour, Developer Center) has a place on the main page. Developer Center? Surely that does not need a link on the front page. It’s a search, not a browse page. I counted: there are more than 35 links on that front page.

Reminds me of something recounted by Marissa Mayer (from Google) at a BayCHI talk. They used to receive an email from a user once in a while. And everytime it would just have a number. Sometimes, the number would be high, and this user would express his displeasure. Later they realized that the number was the number of letters on the Google Home Page.

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Clustering comes to Flickr

It was bound to happen sooner or later. Simple lists are great, weighted lists (or tag clouds) are even better. But as data accumulates, its no longer practical to navigate it through tag lists. Some sort of structure is needed. Back in February I had written about tag-sorting, and how easy it should it should be to cluster tags.

clusters on flickrEnter categories or clusters as they are referred to on Flickr.

How it works: When you click on a tag, you have the option of exploring different clusters related to the tag. For example, summer has several associated clusters:

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