AlamySearch
Alamy released its new search system, AlamySearch on 10th October 2006.
The new system consists of three main components, giving a combined score, to determine image positioning; namely AlamyRank, the Search Engine and the Diversity Algorithm.
AlamyRank
AlamyRank assigns a score to a collection based on the number of times images from a pseudonym have been clicked or purchased in proportion to the number of times they have been viewed by customers.
AlamyRank produces a rank per collection of images (per pseudonym) rather than per image. So a contributor with more than one pseudonym will have been assigned more than one AlamyRank. In the first release, ranks have been calculated from nine months of customer activity. New images added to an existing pseudonym inherit the rank for this pseudonym. New contributors have the median rank assigned to their pseudonyms automatically. This should give them enough visibility from which to calculate a true AlamyRank in time.
The aim is to recalculate AlamyRank on a regular basis at time intervals to be determined from what is learnt over the first launch period.
The Search Engine
The search engine finds images that match the terms entered by the customer. Currently, these words may be in any of the caption, keyword or description fields, or in the pseudonym/agency name. The current search engine uses third party software which cannot be fully tailored to Alamy’s needs. In 2007, the first version of a new search engine will be launched to allow better control over how the system behaves, particularly in terms of relevancy.
The Diversity Algorithm
The Diversity Algorithm comes into play once AlamyRank and the search engine have established which images have the highest score. Its purpose is to ensure that the images returned are inter-dispersed among images of similar rank. This means that search results are not dominated by the collections with the highest combined score and that no one contributor dominates the results. The strength of the Diversity Algorithm diminishes if the gap between the collection rankings is significant. This means that clusters of images from a single collection can appear close together in the search results if there are no competing images available of a similar AlamyRank and/or relevancy score. Given the large number of images on Alamy it is unusual to see this effect on the first few pages of results for most searches.
The Future
To ensure that customers and contributors benefit fully from the new system, feedback will be provided to contributors to help them improve the rank of collections. The goal is to allow contributors to make informed decisions about how to submit and describe their pictures. AlamyRank will become more interactive in the future and will include tools that report customer activity and suggest modifications to submissions and metadata.