Topics
Information retrieval
Finding a recorded item that answers a need. Search engines, relevance, and the structure of the data sit under this subject. It is the field I study.
Within this subject
- Search engines — The libraries and servers that keep an index and answer a query. The names under this subject are systems I have read and worked with.
- Relevance — Whether the result a person receives is one they can act on. Hybrid ranking, similarity, and the structure of the data sit under this subject.
Work
- Public search at country scale — Search a citizen can use: a polling place, a beneficiary record, found in hundreds of millions of rows.
- Concept search before vectors were the default — A books-and-journals search that let people explore by concepts, built in 2018 from phrases and similarity, not from a vector database.
- One catalog, many storefronts — Product search, autosuggest, filters, and per-field similarity for an omnichannel retailer: web, marketplace, and stores.
- Return one record, not a list — From millions of candidates that share an organisation's name and address, return the single best record.
- A move that kept the answers — A production move from self-managed Apache Solr to managed OpenSearch, checked by whether the top results still agreed.
- The team's output — Leading a search engineering group while staying close enough to the system to tell a relevance question from an operations question.
- A new engine, tried on a laptop — A hands-on reading of Luxir, a new hybrid search engine, run from a Mac or Windows laptop without compiling C++.