Archive for November, 2006

Collarity, a Startup of Personalized Search

November 26, 2006 at 11:58 am · Filed under personalization, startup

From the blog of Venture Beat, I got to know there is another startup doing personalized search Collarity.  There are already quite a few startups doing personalized search such as Surf Canyon. 

I tried this version after registering an account. There is a slider called relevance compass, which can let individual users continuously tune the search results from the extremely personalized level through community level to totally population level. This implementation is same as what Microsoft Researcher Susan Dumais did for personalized search with the former intern Jaime Teevan.  After trying some queries and clicking some results, I could how my search results got personalized. Maybe it is still in the early stage of the company. There are some different suggested terms appearing at the bottom of the compass when users move the slider. But the speed is slow and the suggested term is needed to be selected by user for the addition into the query. Here is a paragraph from Venture Beat about the Collarity.

“Levy Cohen, chief executive of Palo Alto-based Collarity, said he got his idea to launch Collarity because it bothered him that Google returns the exact same results to people even if they have different interests. If you’ve searched for information on Linux before, then the search engine should return results relevant to open source, he said. Moreover, if you search for “Java,” the search engine should know whether you’re more likely interested in the computer language, or coffee.”

-Venture Beat

Collarity claims to use the search result of people “like you” to personalize the search results. However, I can only imagine that using other similar users’ interest, we can at most get the community/group level personalization. If we really want the personal level personalization, we should use the user’s own user profile. The idea of Collarity is the collaborative filtering idea, which is extensively used in recommendation systems such as those at Amazon.com and Netflix. But most personalization research in academia is focused on exploiting the user’s own profile. On the other hand, we may combine these two ideas (i.e., item-based and user-based).

One comment mentions that the Collarity is similar with a demo of Yahoo! Research, i.e. Mindset. I find that the interface of Mindset also uses the slider to vary the results from shopping to research.

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Andrei Broder’s Information Supply Talk

November 25, 2006 at 11:02 am · Filed under implicit query, personalization, privacy

From the blog of Geek with Greg, I got to know the talk by Andrei Broder on Information Supply. The slides are available here. 

In the slides, Andrei Broder wants to express his opinion about the next generation web search. In his mind, Information Supply should be the next step of Information Retrieval. He mentions that search engine can infer the user information need and provide relevant information to the user even without the user explicit query. Actually, some research works done by Susan Dumais and Mary Czerwinski on Implicit Query is in this direction.

I think Andrei Broder’s information supply vision matches contextual search/personalized search vision. We need to infer the user information need to understand the user real intention so that we can get better search results.  Currently, the user can easily find satisfactory results from the Web such as finding a homepage of a person or a company. However, the searchers can not find a satisfactory answer for many search tasks too. We need to do research on improving the user search experience or information seeking/acquisition experience.

Andrei Broder gives some general ideas about how the information supply should work. However, he did not give some concrete problems we need to attack. I think here are some problems we will face.

1) What kinds of information seeking activities can personalized search help? I do not think personalized search can help every search. For some search tasks, personalization can even deteriorate the search experience because of imprecise user modeling. Maybe personalization should target at the difficult information seeking activities.

2) How should privacy issue be dealt with? Privacy is a big concern of personalized search because a lot of personal information will be disclosed and can be potentially abused. We need to study how different levels of privacy can fit different individual user’s acceptable privacy levels, how the personalized software architecture should be chosen and how we can implement the personalization systems to guarantee the appropriate privacy protection levels.

3) How should personalized search interact with the user? The user may not be willing to actively participate in the personalization search process. In such cases, we need to consider how to do personalized search in an implicit way. If the user is willing to contribute to personalized search, we need to think a way to get the user involved. Moreover, how should we design the user interface to make the user understand how the personalized search work instead of assuming the user simply accept the black box magic of personalized search. How should we design the personalized search interface to facilitate the personalization process?

Some other questions have been proposed in previous blog entries.  

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Vertical Personalized Search

November 21, 2006 at 11:20 am · Filed under Healia, healthcare, law, vertical search

I talked with a researcher about the personalized information management in the healthcare domain Contextual search is considered as a promising way to improve the information seeking of practitioners in a specific domain. It is interesting to see that vertical personalized search or personalized search in a specific domain has been given a lot of attention.  For example, Healia is a startup to provide personalized health information retrieval service in the health domain.

So far, I have known two domains which are interested in the personalized search, law and healthcare. For both of  these domains,  people have to look for the needle in the haystack and people really care to find relevant information even by interacting with the retrieval system for many iterations for a single information need, which provide the opportunities for the personalized search algorithm to get enough information about the user intention.

However, I also show the concerns about the feasibility of the application of personalized search in these domains. For example, I met a researcher in the law information system company, who complained that lawyers did not want to try the personalized search prototypes because of the privacy concern. Thus I also wonder what the opinion of the doctors about the personalized search is. Thus in order to apply personalized search in a specific domain, we may need to do some survey to investigate whether the people in this domain really like and accept the idea or not.

But I will think vertical personalized search will become more popular in the future, not restricted to healthcare or law domain.

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