Earlier in the year I attended Haystack in Charlottesville, one of my favourite search conferences ever – and almost immediately began to think about whether we could run a similar event here in Europe. Although we’ve only had a few months I’m very happy to say we’ve managed to pull together a high-quality programme of talks for our first Haystack Europe event, to be held in London on October 2nd. The event is focused on search relevance from both a business and a technical perspective and we have speakers from global retailers and by specialist consultants and authors. Tickets are already selling well and we have limited space, so I would encourage you to register as soon as you can (Haystack USA sold out even after the capacity was increased). We’re running the event in partnership with Open Source Connections.

The next week we’re running a Lucene Hackday on October 9th as part of our London Lucene/Solr Meetup programme. Building on previous successful events, this is a day of hacking on the Apache Lucene search engine and associated software such as Apache Solr and Elasticsearch. You can read up on what we achieved at our last event a couple of years ago – again, space is limited, so sign up soon to this free event (huge thanks to Mimecast for providing the venue and to Elastic for sponsoring drinks and food for an evening get-together afterwards). Bring a laptop and your ideas (and do comment on the event page if you have any suggestions for what we should work on).

We’ll be flying to Montreal soon afterwards to attend the Activate conference (run by our partners Lucidworks) and while we’re there we’ll host another free Lucene Hackday on October 15th. Again, this would not be possible without sponsorship and so thanks must go to Netgovern, SearchStax and One More Cloud. Remember to tell us your ideas in the comments.

So that’s three weeks of excellent search events – see you there!

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The first talk was given by Karen Renshaw of Grainger, who Flax worked with at RS Components (she also wrote a great series of blog posts for us on improving relevancy). Karen’s talk drew on her long experience of managing search teams from a business standpoint – this wasn’t about technology but about combining processes, targets and objectives to improve search quality. She showed how to get started by examining customer feedback, known issues, competitors and benchmarks; how to understand and categorise query types; create a test plan within a cross-functional team and to plan for incremental change. Testing was covered including how to score search quality and how to examine the impact of search changes, with the message that “all aspects of search should work together to help customers through their journey”. She concluded with the clear point that there are no silver bullets, and that expectations must be managed during an ongoing, iterative process of improvement. This was a talk to set the scene for the day and containing lessons for every search manager (and a good few search technologists who often ignore the business factors!).

Next up were Christine Bellstedt & Jens Kürsten from Otto, Germany’s second biggest online retailer with over 850,000 search queries a day. Their talk focused on bringing together the users and business perspective to create a search quality testing cycle. They quoted Peter Freis’ graphic from his excellent talk at Haystack to illustrate how they created an offline system for experimentation with new ranking methods based on linear combinations of relevance scores from Solr, business performance indicators and product availability. They described how they learnt how hard it can be to select ranking features, create test query sets with suitable coverage and select appropriate metrics to measure. They also talked about how the experimentation cycle can be used to select ‘challengers’ to the current ‘champion’ ranking method, which can then be A/B tested online.

Pavel Penchev of SearchHub was next and presented their new search event collector library – a Javascript SDK which can be used to collect all kinds of metrics around user behaviour and submit them directly to a storage or analytics system (which could even be a search engine itself – e.g. Elasticsearch/Kibana). This is a very welcome development – only a couple of months ago at Haystack I heard several people bemoaning the lack of open source tools for collecting search analytics. We’ll certainly be trying out this open source library.

Andreas Brückner of e-commerce search vendor Fredhopper talked about the best way to optimise search quality in a business context. His ten headings included “build a dedicated search team” – although 14% of Fredhoppers own customers have no dedicated search staff – “build a measurement framework” – how else can you see how revenue might be improved? and “start with user needs, not features”. Much to agree with in this talk from someone with long experience of the sector from a vendor viewpoint.

Johannes Peter of MediaMarktSaturn described an implementation of a ‘semantic’ search platform which attempts to understand queries such as ‘MyMobile 7 without contract’, recognising this is a combination of a product name, a Boolean operator and an attribute. He described how an ontology (perhaps showing a family of available products and their variants) can be used in combination with various rules to create a more focused query e.g. “title:(“MyMobile7″) AND NOT (flag:contract)”. He also mentioned machine learning and term co-occurrence as useful methods but stressed that these experimental techniques should be treated with caution and one should ‘fail early’ if they are not producing useful results.

Ashraf Aaref & Felipe Besson described their journey using Learning to Rank to improve search at GetYourGuide, a marketplace for activities (e.g. tours and holidays). Using Elasticsearch and the LtR plugin recently released by our partners OpenSourceConnections they tried to improve the results for their ‘location pages’ (e.g. for Paris) but their first iteration actually gave worse results than the current system and was thus rejected by their QA process. They hope to repeat the process using what they have learned about how difficult it is to create good judgement data. This isn’t the first talk I’ve seen that honestly admits that ML approaches to improving search aren’t a magic silver bullet and the work itself is difficult and requires significant investment.

Duncan Blythe of Zalando gave what was the most forward-looking talk of the event, showing a pure Deep Learning approach to matching search queries to results – no query parsing, language analysis, ranking or anything, just a system that tries to learn what queries match which results for a product search. This reminded me of Doug & Tommaso’s talk at Buzzwords a couple of days before, using neural networks to learn the journey between query and document. Duncan did admit that this technique is computationally expensive and in no way ready for production, but it was exciting to hear about such cutting-edge (and well funded) research.

Doug Turnbull was the last speaker with a call to arms for more open source tooling, datasets and relevance judgements to be made available so we can all build better search technology. He gave a similar talk to keynote the Haystack event two months ago and you won’t be surprised to hear that I completely agree with his viewpoint – we all benefit from sharing information.

Unfortunately I had to leave MICES at this point and missed the more informal ‘bar camp’ event to follow, but I would like to thank all the hosts and organisers especially René Kriegler for such an interesting day. There seems to be a great community forming around e-commerce search which is highly encouraging – after all, this is one of the few sectors where one can draw a clear line between improving relevance and delivering more revenue.

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The second day of the event started for me with the enjoyable job of hosting a ‘fishbowl’ style panel session titled “No, You Don’t Want to Do It Like That! Stories from the search trenches”. The idea was that a rotating panel of speakers would tell us tales of their worst and hopefully most instructive search tuning experiences and we heard some great stories – this was by its nature an informal session and I don’t think anyone kept any notes (probably a good idea in the case of commercial sensitivity!).

The next talk was my favourite of the conference, given by René Kriegler on relevance scoring using product data and image recognition. René is an expert on e-commerce search (he also runs the MICES event in Berlin which I’m looking forward to) and described how this domain is unlike many others: the interests of the consumer (e.g. price or availability) becoming part of the relevance criteria. One of the interesting questions for e-commerce applications is how ranking can affect profit. Standard TF/IDF models don’t always work well for e-commerce data with short fields, leading to a score that can be almost binary: as he said ‘a laptop can’t be more laptop-ish than another’. Image recognition is a potentially useful technique and he demonstrated a way to take the output Google’s Inception machine learning model and use it to enrich documents within a search index. However, there can be over 1000 vectors output from this model and he described how a technique called random projection trees can be used to partition the vector space and thus produce simpler data for adding to the index (I think this is basically like slicing up a fruitcake and recording whether a currant was one side of the knife or the other, but that may not be quite how it works!). René has built a Solr plugin to implement this technique.

Next I went to Matt Overstreet’s talk on Vespa, a recently open sourced search and Big Data library from Oath (a part of Yahoo! Inc.). Matt described how Vespa could be used to build highly scalable personalised recommendation, search or realtime data display applications and took us through how Vespa is configured through a series of APIs and XML files. Interestingly (and perhaps unsurprisingly) Vespa has very little support for languages other than English at present. Queries are carried out through its own SQL-like language, YQL, and grouping and data aggregation functions are available. He also described how Vespa can use multidimensional arrays of values – tensors, for example from a neural network. Matt recommended we all try out Vespa – but on a cloud service not a low-powered laptop!

Ryan Pedala was up next to talk about named entity recognition (NER) and how it can be used to annodate or label data. He showed his experiments with tools including Prodigy and a custom GUI he had built and compared various NER libraries such Stanford NLP and OpenNLP and referenced an interesting paper on NER for travel-related queries. I didn’t learn a whole lot of new information from this talk but it may have been useful to those who haven’t considered using NER before.

Scott Stultz talked next on how to integrate business rules into a search application. He started with examples of key performance indicators (KPIs) that can be used for search – e.g. conversion ratios or average purchase values and how these should be tied to search metrics. They can then be measured both before and after changes are made to the search application: automated unit tests and more complex integration tests should also be used to check that search performance is actually improving. Interestingly for me he included within the umbrella of integration tests such techniques as testing the search with recent queries extracted from logs. He made some good practical points such as ‘think twice before adding complexity’ and that good autocomplete will often ‘cannibalize’ existing search as users simply choose the suggested completion rather than finishing typing the entire query. There were some great tips here for practical business-focused search improvements.

I then went to hear John Kane’s talk about interleaving for relevancy tuning which covered a method for updating a machine learning model in real-time using feedback from the current ranking powered by this model – simply by interleaving the results from two versions of this model. This isn’t a particularly new technique and the talk was somewhat of a product pitch for 904Labs, but the technique does apparently work and some customers have seen a 30% increase in conversion rate.

The last talk of the day came from Tim Allison on an evaluation platform for Apache Tika, a well-known library for text extraction from a variety of file formats. Interspersed with tales of ‘amusing’ and sometimes catastrophic ways for text extraction to fail, Tim described how tika-eval can be used to test how good Tika is at extracting data and output a set of metrics e.g. how many different MIME file types were found. The tool is now used to run regular regression tests for Tika on a dataset of 3 million files from the CommonCrawl project. We’re regular users of Tika at Flax and it was great to hear about the project is moving forward.

Doug Turnbull finished the conference with a brief summing up and thanks. There was a general feeling in the room that this conference was the start of something big and people were already asking when the next event would be! One of my takeaways from the event was that even though many of the talks used open source tools (perhaps unsurprisingly as it is so much easier to talk about these publically) the relevance tuning techniques and methods described can be applied to any search engine. The attendees were from a huge variety of companies, large and small, open and closed source based. This was an event about relevance engineering, not technology choices.

Thanks to all at OSC who made the event possible and for inviting us all to your home town – I think most if not all of us would happily visit again.

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I don’t think I’ve been to any other conference with such a strong sense of community or such a high quality of presentations. It was particularly refreshing to be among a group of people with such a level of search expertise and experience that at no point did anything have to be ‘dumbed down’ or over-explained. The attendee list included open source committers from projects including Apache Lucene/Solr and Apache Tika, experts in commercial search, authors of books I’ve long regarded as essential for anyone working in this field, independent consultants and those working for huge global companies. The talks were well programmed, ran exactly to schedule and covered cutting-edge topics. Between these talks the networking was relaxed and friendly and I had a chance to get to know several people in real life that I’ve previously only connected with online.

I think this conference may also have signalled the birth of a new profession of “relevance engineer” – someone who can understand both the business and technical aspects of search relevance, work with a variety of underlying search engines and expertly use the correct tools for the job to drive a continuing process of search quality improvement. Personally, I learnt a huge amount of useful information, made connections with many others in our field and have pages of notes to follow up on.

Last but no means least is to extend my personal thanks to all at OSC who created, planned and ran the event – as a veteran of many events in both technical and non-technical fields I understand very well how much work goes into them, especially if you’re not an event planner by profession! You opened your doors to us and made us all feel very welcome and you all worked extremely hard to make this one of the best conferences I’ve ever attended.

More to follow on day 1 and day 2 soon.

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