文件列表:

LICENSE (11357, 2017-07-28)
Makefile (226, 2017-07-28)
indexer.go (3672, 2017-07-28)
plots (0, 2017-07-28)
plots\dashboard.png (958751, 2017-07-28)
plots\keywords.png (752412, 2017-07-28)
plots\people.png (667719, 2017-07-28)

# Textbox helps you to increase relevance in your search This is an example of use case of textbox to extract keywords, places and people from a news article, so I can increase relevance, on any search that I perform and power visualizations. Read this blog post, to see more background info: https://blog.machinebox.io/increase-the-power-of-your-search-engine-with-textbox-bd5f773a1410  ## Requirements * Textbox (https://machinebox.io/docs/textbox) * Elastic Search and Kibana (https://www.elastic.co) ## Dataset We are going to use a subset of BBCSport News Dataset that could be found here. http://mlg.ucd.ie/datasets/bbc.html http://mlg.ucd.ie/files/datasets/bbcsport-fulltext.zip ## Index the data `indexer.go` will pre-process the articles using `textbox` and index the dataset into Elastic Search You can download and run the inserting using the `Makefile`: ``` $ make run ``` Alternative you can do it manually: ``` # Get the dataset $ wget http://mlg.ucd.ie/files/datasets/bbcsport-fulltext.zip $ unzip bbcsport-fulltext.zip # Run the indexer $ go run indexer.go ``` # Structure of the document on Elastic Search The articles in raw are just a txt files, where the first line is the title, we are going to extract the `title` and use `textbox` to extract `keywords`, `places` and `people`. Pre-Processing with textbox allows to have more structured document as it follows. ``` { id: "123", title: "Radcliffe will compete in London", content: "Paula Radcliffe will compete in the Flora London Marathon...", keywords: ["race director david bedford", "25th anniversary", "..."], places: ["London"], people: ["Paula Radcliffe"] } ``` # Power up the search, getting more relevant results Now that we have more structure data we can perform queries by `place`: ``` GET news_textbox/_search { "query": { "term": { "places.keyword": "London" } } } ``` Or by people: ``` GET news_textbox/_search { "query": { "term": { "people.keyword": "Paula Radcliffe" } } } ``` # Visualize with Kibana And you can plot visualizations to get trends and quick feedback. ## Tag clouds ### People tag cloud  ### Keywords tag cloud  ### Dashboard 

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