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Search is the UI
- 1. Search is the new UI OpenSource Connections @DanielBeach
- 2. @DanielBeach OpenSource Connections ‣ Search strategist @ OpenSource Connections ‣ Elasticsearch + AngularJS video course ‣ Spyglass search UI ‣ New dad
- 4. Powered by Search ‣ Search results ‣ Data visualization dashboards ‣ Recommendation engines ‣ Anomaly detection
- 5. Not your typical search interface. parse.ly
- 6. Search Misconceptions ‣ Search only powers “search pages” ‣ Search is best left to Google ‣ Search is only useful for full-text documents
- 8. Typical Search Inputs ‣ Text entered by a user ‣ Selected filters
- 9. Passive Search Inputs ‣ Current time & events ‣ The user’s location ‣ How recently was the content published? ‣ The popularity of an item
- 11. Talk Overview ‣ Principles of good search ‣ How search engines work ‣ Front-end search patterns
- 13. Search is an opportunity to have a conversation. ‣ Users are telling you what they expect to find on your site ‣ Search is an opportunity to learn about your users / customers
- 15. Principles of Search Design ‣ Values search ‣ Listens to your users ‣ Shows relevant content ‣ Gets out of their way
- 16. Search is about Clarity ‣ The relevancy of the results is more important than the design of the results.
- 17. This is what search should be. amazon.com
- 18. Only Show what is Important ‣ If you have twenty average results, but one result is statistically more important, don’t show the others.
- 20. Accommodate Multiple Types of Searching ‣ Informational users are interested in the breadth of your data ‣ Navigational users want to get somewhere fast
- 22. Bad Search ‣ Invalid results ‣ No results ‣ Confusing result hierarchy ‣ Visually messy results ‣ No clear input or submit
- 23. Good Search Design ‣ Showing relevant data to users ‣ Only shows useful / actionable results ‣ Visually clean results ‣ Differentiated results ‣ Recognizable input and submit
- 24. HOW SEARCH ENGINES WORK
- 25. How humans see text –Arthur Clark
- 26. How a search engine sees text This is called text analysis, and it happens at indexing time.
- 28. Query Analysis A compatible analysis chain must be used for the query string as the indexed content in order for terms to match.
- 29. TERM MEANING Tokenization Splitting text into indexable pieces, called tokens.A word is often an example of a token. Stemming Collapsing words to their root (interpretation, interpreting --> interpret) Inverted index An index of tokens. Maps tokens to document position Term frequency The number of times a token occurs in a document Inverse document frequency Tokens that appear in fewer documents are calculated to be more important (simplified)
- 30. Document Scoring ‣ Score based on number of matches in a document, as compared to the popularity of that term across all documents.
- 31. Types of Boosts ‣ Field boosts ‣ Text matching (title^5 description) ‣ Function scores ‣ Boost newer content ‣ Multiply by % of popularity ‣ …
- 32. Minimum Match ‣ How many of the query terms have to match in order for a document to be returned? ‣ Precision vs recall
- 34. Search patterns
- 35. Search request { "query": { "multi_match": { “fields": ["title^5", "description”], “query": “descender”, "minimum_should_match": "2<-1 5<70%" } } }
- 36. Response { "took": 47, "timed_out": false, "hits": { "total": 2, "max_score": 2.17284, "hits": [ { "_index": "catalog", "_type": "comics", "_id": "84", "_score": 2.17284, "_source": { "title": "Descender", "description": "One young robot’s struggle to stay alive in a universe where all androids have been outlawed and bounty hunters lurk on every planet." ...
- 37. Aggregations
- 38. { query: query, aggs: { "comic formats": { terms: {field: "format"} } } } Aggregations Request
- 39. Aggregations Response { "hits":{ "total":2, "hits":[ ... ], "aggregations":{ “comic types":{ "buckets":[{ "key":"Trades", "doc_count":63}, { "key":"Graphic Novels", "doc_count":35 }, { "key":"Compilations", "doc_count":9 }]}}}
- 40. Filtering { filtered: { query: query, filter: { bool: { must: [ {term: {"illustrator": "Dustin Nguyen"}}; ] } }}}
- 42. Showing relative document counts assignment.uspto.gov
- 43. Autocomplete
- 44. Autocomplete Suggestions ‣ Spelling corrections ‣ More popular phrases
- 45. Autocomplete Request { "query": { "simple_query_string": { "fields": ['title'], "query": baseTerms + '(' + lastTerm + '|' + lastTerm + '*)', "default_operator": "and" } }, "size": 3, "_source": ["title"] }
- 47. Suggestion Request { "query": query, "suggest": { "text": searchTerms, "phraseSuggestion": { "phrase": { "field": "title", "direct_generator": [{ "field": "title", "suggest_mode": "popular", "min_word_length": 3 }] }}}}
- 48. Highlighting
- 49. Highlighting ‣ Highlight search terms ‣ Snippets for large blocks of text
- 50. Highlighting Request { query: query, highlight: { fields: { "title": {number_of_fragments: 0}, "detailed description": {number_of_fragments: 0} } } }
- 51. Highlighting Response { "took":28, "hits":{ "total":2, "max_score":1.44856, "hits":[{ "_index":"catalog", "_type":"comics", "_id":"84", "_score":1.44856, "_source": { "title": "Descender" }, "highlight":{ "title":["<em>Descender</em>"]} } ]}}}
- 53. Load more
- 54. Loading More Results { "query": {"match_all": {}}, "from": resultsPage * 10, "sort": "fieldName desc", }
- 55. Think outside the search box ‣ Search gives you extreme flexibility to return relevant content quickly, given a wide range of inputs ‣ Retrieval and ranking engine
- 57. Search is the new UI OpenSource Connections @DanielBeach