fuzzy-search

问题 I am new to elasticsearch and was looking around fuzzy query search. I have made a new index products with object/record values like this { "_index": "products", "_type": "product", "_id": "10", "_score": 1, "_source": { "value": [ "Ipad", "Apple", "Air", "32 GB" ] } } Now when i am performing a fuzzy query search in elasticsearch like { query: { fuzzy: { value: "tpad" } } } It returns me the correct record (the product just made above) which is expected. And i know that the term tpad matches

问题 I'm wondering if there is some kind of way to do fuzzy string matching in PHP. Looking for a word in a long string, finding a potential match even if its mis-spelled; something that would find it if it was off by one character due to an OCR error. I was thinking a regex generator might be able to do it. So given an input of "crazy" it would generate this regex: .*((crazy)|(.+razy)|(c.+azy)|cr.+zy)|(cra.+y)|(craz.+)).* It would then return all matches for that word or variations of that word.

问题 I have a table with 4 entries. CREATE TABLE tab( name Text ); INSERT INTO "tab" VALUES('Intertek'); INSERT INTO "tab" VALUES('Pntertek'); INSERT INTO "tab" VALUES('Ontertek'); INSERT INTO "tab" VALUES('ZTPay'); Pntertek & Ontertek are fuzzy duplicates of the correctly spelt Intertek. I wish to create a list consisting of fuzzy duplicates and the correctly spelt names. However, I don't want the list to contain the correctly spelt name if there is no fuzzy duplicate found by the LIKE search.

问题 Suppose I have a list:- person_name = ['zakesh', 'oldman LLC', 'bikash', 'goldman LLC', 'zikash','rakesh'] I am trying to group the list in such a way so the Levenshtein distance between two strings is maximum. For finding out the ratio between two words, I am using a python package fuzzywuzzy. Examples :- >>> from fuzzywuzzy import fuzz >>> combined_list = ['rakesh', 'zakesh', 'bikash', 'zikash', 'goldman LLC', 'oldman LLC'] >>> fuzz.ratio('goldman LLC', 'oldman LLC') 95 >>> fuzz.ratio(

问题 I'm checking if there are similar results (fuzzy match) in 4 same dataframe columns, and I have the following code, as an example. When I apply it to the real 40.000 rows x 4 columns dataset, keeps running in eternum. The issue is that the code is too slow. For example, if I limite the dataset to 10 users, it takes 8 minutes to compute, while for 20, 19 minutes. Is there anything I am missing? I do not know why this take that long. I expect to have all results, maximum in 2 hours or less. Any

问题 I have tried this myself for a considerable period and looked everywhere around the net - but have been unable to find ANY examples of Fuzzy Phrase searching via Lucene.NET 2.9.2. ( C# ) Is something able to advise how to do this in detail and/or provide some example code - I would seriously seriously appreciate any help as I am totally stuck ? 回答1: I assume that you have Lucene running and created a search index with some fields in it. So let's assume further that: var fields = ... // a

问题 I have two sets of data. Existing customers and potential customers. My main objective is to figure out if any of the potential customers are already existing customers. However, the naming conventions of customers across data sets are inconsistent. EXISTING CUSTOMERS Customer / ID Ed's Barbershop / 1002 GroceryTown / 1003 Candy Place / 1004 Handy Man / 1005 POTENTIAL CUSTOMERS Customer Eds Barbershop Grocery Town Candy Place Handee Man Beauty Salon The Apple Farm Igloo Ice Cream Ride-a-Long

问题 After successful migration from Neo4j 2.2.8 to 3.0.4 using official faq, full text search does not work as expected. Fuzziness is not that fuzzy as it was before. Example: START n=node:node_auto_index('name:(+Target~0.85)') MATCH (n) RETURN n; Should return nodes with field name that contain work like 85% similar to 'Target'. Before it was matching the following: Target Target v2 After migration: Target Why and how to fix that? 回答1: Reason was that after migration lucene node_auto_index wasn

问题 i have a record saved in Elasticsearch which contains a string exactly equals to Clash of clans now i want to search this string with Elasticsearch and i using this { "query_string" : { "query" : "clash" } } its working perfectly but now if i write "query" : "class" it dont give me back any record so i realize i should use Fuzzy searching so i come to know that i can use fuzziness parameter with query_string so i did { "query_string" : { "query" : "clas" "fuzziness":1 } } but still

问题 Python's new regex module supports fuzzy string matching. Sing praises aloud (now). Per the docs: The ENHANCEMATCH flag makes fuzzy matching attempt to improve the fit of the next match that it finds. The BESTMATCH flag makes fuzzy matching search for the best match instead of the next match The ENHANCEMATCH flag is set using (?e) as in regex.search("(?e)(dog){e<=1}", "cat and dog")[1] returns "dog" but there's nothing on actually setting the BESTMATCH flag. How's it done? 回答1: Documentation