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Solr Fuzzy Suggester and Solr Infix Suggester offer an efficient solution for this. They can be called and filtered via Ajax queries.\"},\"type\":\"paragraph\"},{\"data\":{\"text\":\"The suggester is activated via the XML component SuggestComponent in the solrconfig.xml file, as shown in the following code example:\"},\"type\":\"paragraph\"},{\"data\":{\"code\":\"\u003CsearchComponent name=\\\"suggest\\\" class=\\\"solr.SuggestComponent\\\">\\n  \u003Clst name=\\\"suggester\\\">\\n    \u003Cstr name=\\\"name\\\">mySuggester\u003C\u002Fstr>\\n    \u003Cstr name=\\\"lookupImpl\\\">FuzzyLookupFactory\u003C\u002Fstr>\\n    \u003Cstr name=\\\"dictionaryImpl\\\">DocumentDictionaryFactory\u003C\u002Fstr>\\n    \u003Cstr name=\\\"field\\\">suggest_field\u003C\u002Fstr>\\n    \u003Cstr name=\\\"weightField\\\">weight\u003C\u002Fstr>\\n    \u003Cstr name=\\\"suggestAnalyzerFieldType\\\">text_general\u003C\u002Fstr>\\n    \u003Cstr name=\\\"buildOnStartup\\\">true\u003C\u002Fstr>\\n  \u003C\u002Flst>\\n\u003C\u002FsearchComponent>\"},\"type\":\"code\"},{\"data\":{\"text\":\"By using Solr Fuzzy Suggester and Solr Infix Suggester, users can quickly and easily get relevant results, as they receive suggestions and auto-completion features. Query results can then be filtered to ensure that only the most relevant results are displayed.\"},\"type\":\"paragraph\"},{\"data\":{\"text\":\"By implementing these technologies, websites can offer improved search functionality and a better user experience.\"},\"type\":\"paragraph\"},{\"data\":{\"text\":\"Configuration Example (Syntax Highlighter)\",\"level\":3},\"type\":\"header\"},{\"data\":{\"code\":\"\u003CsearchComponent name=\\\"suggest\\\" class=\\\"solr.SuggestComponent\\\">\\n  \u003Clst name=\\\"suggester\\\">\\n    \u003Cstr name=\\\"name\\\">mySuggester\u003C\u002Fstr>\\n    \u003Cstr name=\\\"lookupImpl\\\">FuzzyLookupFactory\u003C\u002Fstr>\\n    \u003Cstr name=\\\"dictionaryImpl\\\">DocumentDictionaryFactory\u003C\u002Fstr>\\n    \u003Cstr name=\\\"field\\\">cat\u003C\u002Fstr>\\n    \u003Cstr name=\\\"weightField\\\">price\u003C\u002Fstr>\\n    \u003Cstr name=\\\"suggestAnalyzerFieldType\\\">string\u003C\u002Fstr>\\n    \u003Cstr name=\\\"buildOnStartup\\\">false\u003C\u002Fstr>\\n  \u003C\u002Flst>\\n\u003C\u002FsearchComponent>\"},\"type\":\"code\"},{\"data\":{\"text\":\"The image shows what the suggester does: the input does not yield an exact match, and the Solr Suggester returns similar suggestions. There are several ways to determine string similarity. I will mention two here.\"},\"type\":\"paragraph\"},{\"data\":{\"text\":\"1) Fuzzy (Levenshtein distance)\",\"level\":3},\"type\":\"header\"},{\"data\":{\"text\":\"The first possibility is fuzzy, which is based on the Levenshtein distance algorithm.\"},\"type\":\"paragraph\"},{\"data\":{\"text\":\"In JavaScript, it would look like this:\"},\"type\":\"paragraph\"},{\"data\":{\"code\":\"function levenshtein(a, b) {\\n  var t = [], u, i, j, m = a.length, n = b.length;\\n  if (!m) { return n; }\\n  if (!n) { return m; }\\n  for (j = 0; j \u003C= n; j++) { t[j] = j; }\\n  for (i = 1; i \u003C= m; i++) {\\n    for (u = [i], j = 1; j \u003C= n; j++) {\\n      u[j] = a[i - 1] === b[j - 1] ? t[j - 1] : Math.min(t[j - 1], t[j], u[j - 1]) + 1;\\n    } t = u;\\n  } return u[n];\\n}\\n\u002F\u002F a and b are strings\"},\"type\":\"code\"},{\"data\":{\"text\":\"2) Infix (prefix matching and Lucene index)\",\"level\":3},\"type\":\"header\"},{\"data\":{\"text\":\"The second possibility is infix, which is based on prefix matching with tokens in the indexed text. 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