Noen utvalgte bilder fra arrangementet:

Last ned presentasjonene:

• Søkemarkedet i 2014 (PDF)

  Trond Renshusløkken og Espen Klem, Comperio
• Bruk av søketeknologi i rettsdata.no (PDF)

  Kristian Skeie, Forlagsdirektør, Gyldendal Rettsdata
• Om Postens Tilbudssøk.no (PDF)
  Live Marstein, Prosjektleder, Posten Norge
• Hvordan kan du være innovativ i din virksomhet med Google-teknologi? (kommer)

  Christopher Conradi, Enterprise Sales Manager, Google

Noen utvalgte bilder fra arrangementet:

Takket være oppussing på Continental fikk alle frokostdeltakerne starte dagen med litt trappetrim.

Daglig leder i Comperio Trond Renshusløkken ønsker velkommen.

Trond Renshusløkken, Comperio

Espen Klem, Comperio

Kristian Skeie, Gyldendal Rettsdata

Live Marstein, Bring/Posten

Christopher Conradi

Følg oss på Twitter så du ikke går glipp av neste frokostseminar.

Prince Sverre Magnus – Screenshot from the Norwegian Royal Families website.

Lately, there have been some parties. For example yesterday, when we celebrated the 17th of May – Norway’s day of independence. Then we sat down, after hours of parades and sausage eating and suddenly realized that we couldn’t remember the name of the youngest member of the Norwegian Royal Family. “Magnus-something-or-other” was the closest we came.

Then the solution was, as usual, to pick up the iPhone and search for “the Royal Family” on Google. Not only did we find out that his name is Sverre Magnus, but we also got to see pictures, his birthday, what his sister is called, and so on and so forth. Also the complete list of the royal family gave us new topics of conversation and maybe more answers then we did sought.

And why do I use the blog to share an uninteresting, private Royal-Family conversation I had at the 17th of May? Simply because I every day see how important good search is as a problem solver, and a way to find the answer we’re looking for.

In a workplace, we have lots of information available: both internal information and information through, for example, Google or Bing. How much time do we spend talking about things we cannot find the answer to? Or how much time do we spend sitting alone wondering? Or how much time do we spend digging through old documents, presentations, customer records, and so on.

If we have good internal search at work, we can quickly find answers, find richer answers then we were looking for, and find colleagues that can give the answer to us.

And the search should be as easy as my 17th of May-solution, to grab the phone out of my pocket.

What is your experience with internal search?

In the current flame war between Google and Bing, there is a good amount of pie-throwing going on around the internet. But in the process, some very interesting tech stuff has surfaced as well. We’ve got a glimpse on one of the many components Bing is using as a measurement of relevance, namely click-stream data from real users.

Disregarding the Google vs. Bing dispute; the use of click-stream data (aka browser usage statistics), is very interesting in a search engine perspective. This is because relevance of search queries is often described as a combination of the precision of the results and the recall of the query, and click-stream data can help increasing them both.

Here’s one of the reasons why.

If you spend a lot of time on a particular web site, you have probably used its search engine. Quite often, you can choose to search through the site using Google or Bing. But a reason why it makes sense to use the site’s own search engine is that in theory, the particular site can always build a better search experience than what anyone else ever could. They can rank the documents using important internal metrics such as e.g. upvotes (Reddit), social distance (LinkedIn) reputation (Stack Overflow), and retweets (Twitter). The list goes on.

Now. If you happen to be able to watch what users do on these particular web sites, you would in fact be able to lift some of that domain-specific data (upvotes, distance, reputation, and retweets) into your own machinery. Perhaps not directly, but at least indirectly.

If someone searches on Reddit for a certain comment thread, their search engine will (supposedly) produce the best match, ranked according to how many upvotes and comments that particular thread has accumulated. Two things are of interest:

1. The user is quite likely to visit a page that was returned high up in the results.
2. The URL to the results is likely to contain something like “search=TERMS” or “query=TERMS”.

If you happen to collect browser usage statistics you can draw the conclusion that the documents that the user clicked on are highly relevant according to the site’s internal metrics – whatever those might be. Better yet, as you can analyze the URL to the actual search form you also know the particular query terms that the user typed to find these documents. And you can adjust your search engine accordingly.

Simply put, you have now leveraged a web site’s internal data in your external search engine. Consequently adding to the precision of the results using a previously unreachable metric.

Additionally, this tactic will open up more of the “invisible web”. For example, it is not uncommon for government sites to contain big amounts of data, but the only way to get to it is by running queries through an often poorly designed search form. Links into the data sets are rarely provided, so the actual data remains hidden from the search engines.

Until now, as click-stream data allows the search engines to discover it by piggybacking on users’ browsing sessions. Thus, adding to the recall of the queries.