Cambridge Search Meetup – Search for publication success and low-cost apps

After a short break the Cambridge Search Meetup returned last night with our usual mix of presentations, questions, networking, beer and snacks. We had a few issues with the projector and cables (one of these is on the shopping list for next time) so thanks to both presenters and audience for their patience!

First up was Liang Shen with a description of Journal Selector, a system for helping those publishing academic papers to find the correct journals to approach. The system allows one to copy and paste a chunk of a paper to a website and find which journals best match the subject matter, based on what they have published in the past. Running on the Amazon EC2 cloud the service indexes journals from feeds, HTML webpages and other sources, processes and stores this data in Amazon’s Hadoop-compatible database, indexes it with Apache Solr and then presents the results via the Drupal CMS. The results are impressive, allowing users to see exactly on what basis the system has recommended a journal to approach. You can see the presentation slides here.

Next was Rich Marr, who bravely offered to live-code a demonstration of his low-cost prototyping methodology for startups needing both NoSQL data storage and search across this data. In only 20 lines or so of code he showed us how to use Node.js to build a simple server that could accept messages (over Telnet, although HTTP or even IMAP would be as easy), store them in a CouchDB database and index them for searching (using a different message) with Elasticsearch. Rich’s demo prompted a lively discussion of how commoditized and componentized search technology is becoming, with open source components that allow one to build a prototype search engine in minutes.

Thanks to both our speakers – and the Meetups continue, with Rich Marr’s own London Open Source Search Social meeting on Tuesday 23rd October, and in Cambridge the Data Insights Meetup where I’ll be talking on November 1st.

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