Enterprise Graph Search

Facebook will soon launch their new Graph Search to the general public, and it has received a lot of interest lately.

With graph search, the users will be able to query the social graph that millions of people have constructed over the years when friending each other and putting in more and more personal information about themselves and their friends in the vast Facebook database. It will be possible to query for friends of friends who have similar interests as you, and invite them to a party, or to query for companies where people with similar beliefs as you work, and so on and so forth. The information that is already available, will all the sudden become much more accessible through the power of graph search.

How can we bring this to an enterprise search environment? Well, there are lots of graphs in the enterprise as well to query, both social and other types. For example, how about being able to query for people that have been members of a project in the last three years that involved putting a new product successfully to the market. This would be an interesting list of people to know about, if you’re a marketing director that want to assemble a team in the company, to create a new product and make sure it succeeds in the market.

If we dissect graph search, we will find three important concepts:

  1. The information we want to query against don’t only need to be indexed into one central search engine, but also the relations and attributes of all information objects need to be normalized to create the relational graph and have standard attributes to query against. We could use the Open Graph Protocol as the foundation.
  2. We need a parser that take human language and converts it to a formal query language that a search engine understands. We might want to query in different human languages as well.
  3. The presentation of results should be adapted to the kind of information sought for. In Facebook’s example, if you query for people you will get a list of people with their pictures and some relevant personal information in the result list, and if you query for pictures you will get a collage of pictures (similar to the Google image search).

So the recipe to success is to give the information management part of the project a big focus, making sure to create a unified information model of the content to be indexed. Then create a query parser for natural language based on actual user behavior, and the same user studies would also give us information on how to visualize the different result set types.

I believe we will see more of these kind of solutions in the coming years in the enterprise search market, and look forward exploring the possibilities together with our clients.

Tagging, Social Networks, Interaction and Findability

Events the past days has got me thinking about the power of social tagging and its connection to findability. Thoughts that commend me to writing my most personal (and perhaps off topic) post yet on this blog. (All thoughts expressed in this post are my own and do not necessarily reflect the opinions of my employer.)

Rumors about the shut down of Delicious have been circling the web. Even though it is still unconfirmed from Yahoo, my Twitter feed has been filled with comments about how to save your bookmarks, export bookmarks to other services, petitions to Yahoo about saving Delicious or making it open source.

Traditionally when talking about user tagging of content the topic is re-finding things. Users tag information on the web or an intranet in order to be able to find their way back to them. However most of the comments that I’ve seen about Delicious being shut down has nothing to do with this. As I see it, users don’t claim to be missing the bookmarks themselves, but the social network, research, collaboration and search capabilities that came with the bookmarking service. Delicious seems to have emerged from a service that helps you bookmark your things for re-finding them to a service that helps you find new things based on the tagging of others. Tagging, or social bookmarking may very well have started as a way of re-finding your information but has grown into a new way of discovering information, in parallel to search. (Maybe that is an explanation to the tweets wishing for Google to buy delicious from Yahoo?)

So, tagging can not only help you re-find your own stuff but also explore new things and spread information. One good example of this is what is currently going on in the swedish Twitterverse. It all started with one journalist’s discussion with her friends about the disbelief towards the women accusing Julian Assange of sexual assault. It quickly turned into so much more; a profound discussion about the fine lines of sexuality, what is OK, what we want and like and how to say no. Using the hash tag #prataomdet swedish twitter users are writing about and discussing their experiences in an effort to change the cultural climate so that people talk about it, start communicating with each other about sexuality. You can easily follow all the tweets real time and read blog posts on the topic at prataomdet.se. Many of the major news sites have now started reporting on this as well after the massive activity on twitter. (For non-swedish speaking readers an effort has also been made to start discussions in English as well at #talkaboutit on twitter.)

The feed in itself is thought provoking and can easily keep you busy for hours. Besides the content and openness of the discussions I find something else amazing. In a matter of hours this one tag joined together users, many of whom have never interacted with each other before, helping them share and find new information about something that was unspoken of earlier. Combining the power of social networks and tagging made this possible.

I usually write very different sorts of blog posts at this blog. This one time I just wanted to revel over the amazing possibilities for interaction that technology offers us today. Then maybe the next step is to think about how to tap into this power of interaction and how findability within the enterprise can benefit from this as well. In the mean time I recommend reading about What social networks reveal about interaction or how Västra Götalands Region are currently working on incorporating user tagging into their metadata.

Enterprise Search 2.0?

While visiting Enterprise Search Summit in San Jose I realized that enabling Enterprise 2.0 within enterprise search is the hottest trend at the moment. Is it Enterprise Search 2.0?

Andrew McAfee who coined the term Enterprise 2.0 and has released a book on the subject, spoke about how to use altruism to develop the enterprise. People are wired to help and if we stop obsessing about the risks and lower the bars for how people can help each other it is possible to make this work within a corporate environment.

He also spoke about how process control and how much workflow control. How much do we really need? Make it easy to correct mistake instead of making it hard to make them. With regards to innovation he pointed out that we need to question credentialism and build communities that people want to join. To leverage the intelligence aspects within the enterprise we should explore and experiment with collective intelligence such as prediction markets and open peer review processes. All in all make it easy for people to interconnect.

Very high improvement in access to knowledge, internal experts, satisfaction, increased innovation and customer satisfaction.

I also recommend to read Price Waterhouse Coopers Technology Forecast Summer 2008 to get a good overview of the available tools and technologies.

So how does this impact enterprise search? Search can be made to be the facilitator for Enterprise 2.0. Of course it is possible to index and make all blogs, wikipedias, tweets (yammer), online communities and social networks searchable, but that is only one way to make it this new environment more findable. If someone tweets or blogs about information we should use that information to impact on the search results and ranking. We could also track user behavior on a site to make certain information more visible with regards to implicitly expressed interests.

How Many Users Can You Afford to Annoy?

The second keynote at the Human Computer Interaction conference in Lancaster was given by Jared Spool who talked about Breaking through the invisible walls of usability research. Jared is a very inspiring and entertaining speaker. If you have the chance to listen to him, take it!

One of the things he talked about was the fact that the usability techniques that are widely used today were in fact not designed for large amounts of users. We have all kinds of data about the users’ behaviors online, but can we really use that data in a productive way? As Jared said;

“there is a big difference between data and information, we don’t know what inferences to make from the data we have.”

He also gave examples from a couple of large american ecommerce sites that have millions of users every day. With traditional usability measures you, according to Jacob Nielsens report, can identify 80% of the usability problems with as few as five users. But if you have one million customers, then you could say that 200.000 of the customers would be annoyed. Imagine how much money’s worth of lost revenue 200.000 users is. So how many nines to we need? (90, 99, 99,999?) How many percent is enough? It is apparent that we need to find methods that can solve these problems with usability evalutations and testing.

Jared Spool visualizes how few users actually spend money on an ecommerce site, and how few users the company relies on for their revenue.

Jared also talked about the consequences that web 2.0 have had for web applications and communities. He talked about what things that make people want to use “extra functionality”, as for example review functionality; what things delight people. Things that are excitement generators today soon come to be expected in every application. And when, as Jared said, HCI becomes HHHHHCI; when social networks are widely used, things that delight us or aggravate us, spread very fast. So instead of thinking about the five user rule, think about this next time you plan a release of a new product or application: How many users can you afford to annoy?