Fuzzy duplicates stata. Are all of the records but one errors? .

Fuzzy duplicates stata , 0. 3. With that goal in mind, let me introduce you to recordlinkage package. corn Abstract The duplicate elimination problem of detecting multiple tuples, which describe the same real world entity, is an important data cleaning problem. If membership in a specific condition is binary (i. Any idea how I could do this? Thanks The researcher transforms variables either into crisp or fuzzy sets. edu {surajitc, vganti}@microsoft. Crisp sets record a value of 1 to cases that are members in a given condition and 0 to non-members. We illustrate an important application of fuzzy string matching, namely duplicate detection. Therefor, I looked for a command in Stata that can match the string variables. Featured content New posts New Excel articles Latest activity. Login or Register by clicking 'Login or Register' at the top There is a mass of approximate Understanding challenges with customer data. You cannot 100% rely on it but it help you to narrow down your search result and make the query fast. I need to identify the name of vendors who are similar to each other. Highly Influenced. The Original Record Number of the first fuzzy duplicate in each group is used to identify the group. Reference. Feb 28, 2024. Fuzzy Wuzzy logic on a single pandas data frame to replace similar values with the most occurring instance. The vagueness and uncertainty involved in detecting fuzzy duplicates make it a niche, for applying fuzzy reasoning. I'm asking how to perform deletion of duplicates (and retaining one record per identified duplicate records group), according to already identified duplicate record pairs (multiple duplicate record pairs per same entity). Removing duplicates, conditional on a value within a column. For example, “Janson” is the name in record number 3 in the I'm attempting to find duplicate entries based of a several variables, some numeric, but mostly string variables. In short, we use fuzzy merge when the strings of the key variables in two datasets do not match exactly. No output table is produced if processing is terminated. Removing Fuzzy Duplicates in R. Everything I've found with compged, soundex, etc. You can test individual character fields in a table to identify any fuzzy duplicates in a field, and produce output results that group fuzzy duplicates based on a degree of difference that you specify. Both the ID and ED file contains unique identification code This Stata FAQ shows how to check if a dataset has duplicate observations. csv') # Drop exact duplicates df_clean = df. at & t inc 3. -matchit- can replicate this functionality but in several steps. 430 1 1 gold badge 4 4 silver badges 13 13 bronze badges. Excel Articles. A person is associated with one or more records (personID). for My question is on how to create a function that would take the list with fuzzy duplicates in input and output a list of combined persons. It’s like looking through almost closed eyelids, with your vision becoming fuzzy and it’s hard to distinguish small differences between words. Home; Forums; Forums for Discussing Stata; General; You are not logged in. m:m merges m:m specifies a many-to-many merge and is a bad idea. Bena Brin Stata: how to duplicate observations under certain conditions. There is no silver bullet that will work for each and every case. Fuzzy match strings in one column and create new dataframe using fuzzywuzzy. For instance, if you do not care about the difference between “My Big Corporation” vs “The Small Company, part of My Big Ideally I would like only to output the original name if there was a fuzzy duplicate found by the LIKE. Lets open sec1_a_cleaned. gov) • Laura Hughes (lhughes@usaid. For each unique Variable B, I want to keep the row with highest similarity score. dta in our Stata: use sec1_a_cleaned. When accounting for the bloating effect of multiple copies of these duplicate ads, these duplicates account for 7. 33 would indicate something like “more out than in, but still somewhat in” I am looking for a strategy to remove inexact duplicates, and fuzzy matching seems to be the method of choice. sql; sqlite; fuzzy-search; sql-like; sqlite3-ruby; Share. Email. WRatio is a combination of multiple different string matching ratios that have different weights. 2007 "3COM CORP. The first few records from the restaurant dataset. ', 'Antila,Thomas' and 'ANTILA THOMAS', 'Z_SANDSTONE COOLING LTD' and 'SANDSTONE COOLING LTD' etc. We start by running the duplicates report command to see the number of duplicate rows in the dataset. We generalize this idea using a geometric interpretation of distance functions in a fine-grained (per-record) manner, in order to learn “safe” fuzzy-join programs that can maximize recall while ensuring high precision (Section 3. I would like to merge the two datasets using the only available option: the name of the firms in the two datasets. How to see if all values within group are unique/identify those that aren't. This user-written command is nice because it creates a variable that captures all the information needed to replicate any deleted In order to fuzzy-join string-elements in two big tables you can do this: Use apply to go row by row; Use swifter to parallel, speed up and visualize default apply function (with colored progress bar) Use OrderedDict from collections to get rid of duplicates in the output of merge and keep the initial order Identify fuzzy duplicates from a single column and create a subset containing records of fuzzy duplicates using R. rheem mfg co 6. I have a table which contains name of vendors along with their other details such as address, telephone no etc. I referenced this question in my post. starbucks corp 7. I have tried using the -matchit- function to inspect the string variables one-at-a-time to look for duplicates, and the -duplicates- function to work with the numeric variables. The tool searches for fuzzy duplicates that differ in 1 to 10 characters and recognizes omitted, excess, or mistyped symbols. Notes. A little twist to duplicate To clarify, I'm not asking for a way to do the fuzzy match or identify duplicates, it's already done and results are in the table B. For example, for a test field with 50,000 values, a Result Size (%) of 1 would terminate processing if the results exceeded 500 fuzzy duplicates. Introduction to Deduplication in Apache Spark Data deduplication is essential in use cases involving customer data, user accounts, and Identify fuzzy duplicates from a single column and create a subset containing records of fuzzy duplicates using R. dish network corp 4. Sep 14, 2023. How to remove duplicate observations in Stata. Thus individuals can be more or less a member of a particular set (e. Fastest way to detect and append duplicates base on specific A Common Industry Problem: Identify Fuzzy Duplicates in a Data with Million Records A clever technique to optimize the deduplication algorithm. Select a node and expand the group. Show more. The Stata Journal 19 (2), 435-458, 2019. Usually when you merge, you have a unique ID — or at least enough of one that you can salvage. Approximate de-duplication. I need to detect observations that 1. Fuzzy duplicates, also known as near-duplicates or approximate duplicates, are records within a dataset that represent the same entity or object but have slight variations in their attribute values. dta, we need to determine the unique identifiers. Add to Mendeley. This is followed by duplicate reports id, which gives the number of replicate rows by I am working with a survey data set of over 300 variables and near 10,000 observations. , F4. My issue: many articles and SO questions deal with matching a single string against all records in a database. the main difference in favor of -reclink- over -matchit- was that it applied the bigram fuzzy matching to a set of columns of each datasets in one step (allowing also different scores for each pair of columns) . Step 4: Perform Fuzzy Matching. 4. To set the correct value to all similar records, click on the Check icon in the Action column on the line with the correct entry. I have been unable to get the same results between fuzzy RD with covariates and ivregress 2sls. is for fuzzy matching two different variables or fuzzy matching two different datasets. This value will be automatically assigned to all items of the node and you will see it in the Correct Value column:; If the node doesn't contain Dear all, with the command (duplicates list) we can find observations which are completely (100%) same. How can use fuzzy matching in pandas to detect duplicate rows (efficiently) How to find duplicates of one column vs. The fuzzy join to the same Table gives you a column with a Table Forums for Discussing Stata; General; You are not logged in. But if they disagree on other variables, you need to find out why. Stata: from a bunch of duplicates, keep a particular one. Fuzzy sets, in contrast, allow the Fuzzy Duplicate is a special kind of Duplicate Key detection which is used to identify similar records in Character fields. To understand the need and importance of fuzzy match processes, we must first address the challenges with customer data – specifically customer contact data such as names, phone numbers, email addresses, and location data that comes packed with challenges like duplicate entries, missing values, questionable Now I have two variables that are the same, namely, "Name of the firm", and they are duplicates. In this Eliminating Fuzzy Duplicates in Data Warehouses Rohit Ananthakrishna 1 Surajit Chaudhuri Venkatesh Ganti Cornell University Microsoft Research [email protected] { surajitc, vganti } @microsoft. -matchit- gets me 2016 Swiss Stata Users Group meeting Bern November 17, 2016 Julio D. R finding records without duplicates in long form data. 5. I want to identify and drop these I want to de-duplicate based on a fuzzy match of names, ideally using a repeatable process, but I understand that some manual review is probably required. However, I have an exception to make. Overview. Below are the supplier names as example, which are exact duplicates as well as near duplicates, how can we identify this is with R, 3M 3M Company 3M Co A & R LOGISTICS INC AR LOGISTICS INC A & R LOGISTICS LTD ABB GROUP ABB LTD ABB INC how do I tag these into one group by fuzzy logic to normalize the names. 2) and study the robustness of our results to token replace- Fuzzy row matching helps to remove duplicates and introduces consistency to your data. Expecting it to be smart like a human and jump to a conclusion that nearby values should be treated as the same is expecting too much. By nondisjoint-groups, I mean those entities (in my case co_code) that are in both categories. Hello! I have a list of 20k names and I am trying to find the fuzzy duplicates on the same column Like: Company Waterfall Company Waterfll Company Forums. 1). This option can be found [] strpos()—Findsubstringinstring Description Syntax Remarksandexamples Conformability Diagnostics Alsosee Description strpos(haystack,needle /* mark duplicates using Stata’s built-in functionality */ duplicates tag ecusip_id, gen(dup_2) summ dup_2 count if dup_2 !=0 summ dup This is where it starts to get fuzzy for me. Remove duplicate approximate word matching using fuzzy python. All are user written and can be installed using ssc install How to work with found fuzzy matches Correct all misprints in the duplicate node. Stata: If all observations unique, skip code. Facebook. Consider the following example: In this dataset, records 1 and 2 are How can i delete duplicates based on fuzzy matching or other way of detecting similarity but ensuring that row with similar address will be deleted only if first and last name are matching also? Example data: First name | Last name | Address 0 John Doe ABC 9 1 John Doe KFT 2 2 Michael John ABC 9 3 Mary Jane PEP 9/2 4 Mary Jane PEP, 9-2 5 Gary Young 82 fuzzy: A program for performing QCA in Stata because unlike crisp sets, fuzzy sets can range between 0 (completely exclusive) and 1 (completely inclusive). For example, if locals use different names for the same place, an AI model trained on geographic or cultural data might correctly group them, whereas traditional fuzzy matching would likely I have two datasets each containing data on certain firms. Publisher Summary. ” Rule-Based Deduplication: This technique involves defining specific rules or criteria to identify duplicates. Daily Dose of Data Science. Some records for a given person may be inexact duplicates, which I identify because they have similar (not exact) start and end dates. These variations can arise from data entry errors, inconsistent formatting, or different data sources. Here is just a sample data set: the MIA to also leverage the fuzzy duplicates, instead of the reference trap sequence alone (Sec. . This chapter develops an algorithm for eliminating duplicates in dimensional tables in a data warehouse, which are usually associated with Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. I am looking to deduplicate the entire database at once. More. The former would be a linear time problem (comparing a value against a million other values, ieduplicates identifies duplicates in ID variables, To install ieduplicates, as well as other commands in the iefieldkit package, type ssc install iefieldkit in Stata, as this command is a part of the iefieldkit package. 6. This can eliminate unwanted variations, making it significantly easier to identify similar * Example generated by -dataex-. I've been testing the fuzzy duplicate detection, and it works great at tagging these cases. 25. Undead. Similarity, scoring often involves a Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company This chapter studies different approaches that have been proposed for XML fuzzy duplicate detection, and shows that the DogmatiX system is the most effective overall, as it yields the highest recall and precision values for various kinds of differences between duplicates. Hi All, I am looking for an equivalent of duplicates tag/report that will work on inexact or substring matches in string data within a single variable. Viewed 3k times 1 . Choose Table1 for the Left Identify Fuzzy Duplicates in a Dataset with Million Records A clever technique to optimize the deduplication algorithm. Oct 26, 2024. Previous Forums for Discussing Stata; General; You are not logged in. Identify Fuzzy Duplicates at Scale. Pavel Nasevich. SQL Query Find Exact and Near Dupes. ID contains location and ED contains emissions from such installations. Ananthakrishna et al. I have a huge table containing such records,so, I'm just producing a sample. A Common Industry Problem: Identify Fuzzy Duplicates in a Data with Million Records. datadate) or to carry the month of the datadate forward within each firm for subsequent months where datadate is missing For the fuzzy matching of company names, there are many different algorithms available out there. WRatio, so your having a total of 4,900,000,000 comparisions, with each of these comparisions using the levenshtein distance inside fuzzywuzzy which is a O(N*M) operation. Copy link. What's new. The first example will use commands available in base Stata. 38. It allows you to correct misprints automatically or manually directly in search results. This is a key idea behind Auto Hi All, I am looking for an equivalent of duplicates tag/report that will work on inexact or substring matches in string data within a single variable. kmart corp I have a somewhat similar question related to the original post but it has to do with fuzzy RD. Hot Network Questions Implement Uiua's 'tuples' function Duplicate records kill productivity of marketing and sales teams, increase costs, and ruin customer experience. However, if a group owner is a fuzzy duplicate of another value in the test field, the two values will appear together in a group somewhere in the results. I know this is very wrong but I want something along the lines of: SELECT name FROM tab WHERE name LIKE 'Z_Pay' IF ATLEAST 2 name LIKE 'Z_Pay' Thanks in advance for any help you can give me. Are all of the records but one errors? Dear Stata members I would like to remove the "nondisjoint-groups" from my sample. " Fuzzy duplicate output results. It provides all the tools needed for . ” and “123 Main Street. 71. New posts. Stata: Counts non-duplicate rows as duplicates. When the specified variables are a set of explanatory variables, such a group is often called a covariate pattern or a covariate class. g. fuzz. I am aiming to modify this code so I can check for row duplicates in a single dataframe. Avi Chawla. There are two methods available for this task. Any hint on how to find fuzzy duplicates in single column would be appreciated! Thanks :) postgresql; duplicates; self-join; pg-trgm; Share. I am wondering if there is a way to let paperless-ngx delete these duplicates? In most cases, the duplicate confidence is 100? It doesn't seem to be an option in the docs, and I am wondering if this is maybe something planned for future? Thanks! Beta Was this translation Let's say I have the following data: id disease 1 0 1 1 1 0 2 0 2 1 3 0 4 0 4 0 I would like to remove the duplicate observations in Stata. The fuzzy duplicate groups provide you with a starting However, if you tried to remove duplicates directly, standard functions (e. Output can be like below, also fuzzy-duplicates, and suggesting that Edit-distance( , )≤1 likely joins overly aggressively and is actually not “safe”. Given your task your comparing 70k strings with each other using fuzz. We will also explore how deduplication contributes to improved machine learning pipelines and overall data quality. I was successful in finding exact duplicate vendors, but it becomes difficult with fuzzy duplicates. The example below shows the output results produced by testing for fuzzy duplicates in the Last Name field of a table. The keyword here is similar – there are already lots of tools for finding exact matches. wal mart stores inc 9. Raffo Senior Economic Officer WIPO, Economics & Statistics Division Data consolidation and cleaning using fuzzy We may use the fuzzy match / fuzzy merge technique in that case. Non-exhaustive means that individual fuzzy duplicate groups in the results may not contain all the fuzzy duplicates in a test field that are within the specified degree of difference of the group owner. dta, clear. One approach is to use soundex . Sometimes, however, no unique identifier was collected, and you’re left searching for alternative ways to link two datasets. To install: ssc install dataex clear input str17 CUSIP_stata long CIKNumber_stata float Year str76 Company "885535104" . There are a few commands that can help with fuzzy mergeing in Stata. To merge it with sec1_b. My practical suggestion is to use minsimple if you do not care about what does not match as much as you care of what you actually match. hvm extended stay hotels llc 5. Because the > street_names can have some typos for some street_numbers, when I collapse > some streets appear duplicated within cities (see example bellow) > Duplicated street_names After the fuzzy match, my data looks something like this. Once records are identified as having similarities, they are gathered into groups called Fuzzy Groups and ranked according to their similarity degree – the more similar the These methods allow us to address both exact and fuzzy duplicates in large datasets efficiently. The second example will use a user-written program. It uses fuzzy wuzzy to fund duplicate rows in 2 dataframes. The output results are arranged in groups identified as 2, 3, and 6. 0. Outline. Author links open overlay panel Rohit Ananthakrishna 1, Surajit Chaudhuri, Venkatesh Ganti. Eliminating Fuzzy Duplicates in Data Warehouses Rohit Ananthakrishna1 Surajit Chaudhuri Venkatesh Ganti Cornell University Microsoft Research rohit@cs. , cases are either members or non-members in the condition), the respective set is called crisp set (Ragin, 2008). C de Chaisemartin, X D’haultfœuille, Y Guyonvarch. I am using the command MATCHIT (for the first time) from Julio Raffo to fuzzy match 2 data-sets. com) Tim Essam (tessam@usaid. For example id disease 1 1 2 In the modern digital world, where the volumes of electronic texts are growing exponentially, the problem of detecting duplicates in textual documents becomes extremely relevant and important [1, 2]. drop_duplicates() Fuzzy matching Sometimes, duplicates in a dataset may not be exact matches due to variations in data entry or 6 record linkage utilities 2. Fuzzy differences-in-differences with stata. We can clearly see that the first and second records correspond to the same restaurant, and similarly, the third and fourth records correspond to the same restaurant. Any help with this question would be greatly appreciated. 3 Excerpts; Save. Structure-based inference of xml similarity import pandas as pd # Load data df = pd. read_csv('data. "distinct()") would state that there are no duplicates in this dataset, seeing as all rows have some unique element. You can browse but not post. I could do drop if column == 253, but I have many other duplicates and I would like to do another thing than just looking at the data to report the corresponding column value. To perform Fuzzy matching, click the Fuzzy Lookup tab along the top ribbon: Then click the Fuzzy Lookup icon within this tab to bring up the Fuzzy Lookup panel. The following articles are merged in Scholar. For example, Consider Fig 10. Their combined citations are counted only for the first article. > > Is there a command to do some sort of probabilistic/fuzzy string comparison > among the rows of a string variable (similar to what reclink does but > with-in the Python Pandas - Fuzzy duplicates matching. Before handling fuzzy duplicates, it’s crucial to normalize your text data. 5% of our data! By allowing fuzzy deduplication, we’ve found twice as many duplicate documents as before. There are various alternatives to the much more difficult problem you have, including soundex and fuzzy matching. The master file has 5606 observations and the using file has 5387 LTD' and 'CANON INDIA PVT. I want to drop all possible obs_number values for all duplicates. Customer relationship management I have one variable that is a list of schools. Unfortunately, the spellings of firm names are different across the two datasets. For instructions and available options, type help ieduplicates. Modified 6 years, 2 months ago. Because the > street_names can have some typos for some street_numbers, when I collapse > some streets appear duplicated within cities (see example bellow) > Duplicated street_names between cities would be OK. Identify Fuzzy Identify Fuzzy Duplicates at Scale A clever technique to optimize the deduplication algorithm. duplicates works on exact equality, no more, no less. Ask Question Asked 6 years, 2 months ago. Fuzzy matching will return a match when two fields are alike (similar). gov) FUZZY MATCHING: COMBINING TWO DATASETS WITHOUT A COMMON ID merge 1:1 id using In Stata terms, duplicates are observations with identical values, either on all variables if no varlist is specified, or on a specified varlist; that is, 2 or more observations that are identical on all specified variables form a group of duplicates. I have been trying to research different methods in R that are able to de-duplicate rows based on "fuzzy conditions". 597). I need to identify such fuzzy duplicates and create a new subset containing these records. sql; duplicates; fuzzy CaseWare IDEA® Version 10 introduced an Advanced Fuzzy Duplicate task, which identifies multiple similar records for up to three selected character fields. Note that nowadays some people are using machine learning to find a good matching function. In an m:m merge, observations are matched within equal The similarity scores are explained in the help section “Notes on the different scoring options”. Eliminating Fuzzy matching can identify duplicates even if there are slight variations in spelling or formatting, such as “123 Main St. New posts Search forums Board Rules. In this post I mostly want to talk about how to search for duplicates, given that a matching function has been established. 1. Chapter 51 - Eliminating Fuzzy Duplicates in Data Warehouses. Pavel Nasevich Pavel Nasevich. Expand. Remove duplicate entries after fuzzy matching between tables. In an ideal world I'd like to . . LTD. all the other ones without a gigantic for loop of converting row_i toString() and then comparing it to all the One significant advantage of using AI over fuzzy matching is its ability to leverage extensive knowledge bases, enabling it to recognize context-specific variations more accurately. asked Duplicate citations. Fuzzy Duplicates: 10 Advanced Ways to Identify & Deduplicate Customer Master Data for google sheets. Improve this question. Fuzzy data deduplication is needed in various applications because duplicate records can cause numerous problems, negatively impacting the effectiveness of these applications. reconciling duplicates in one column with various values in another column. Our fuzzy deduplication found 2,244 duplicate documents, or about 2% of the total dataset. Search in General only Advanced Search Search. Our aim is to find all the The matching function entirely depends on your application. 46: 2019: TWOWAYFEWEIGHTS: Stata module to estimate the weights and measure of robustness to Fuzzy duplicates impede data analysis, which relies upon data referencing real-world entities in a consistent manner. I have a Dataframe like this: make model 0 allard K1 1 alllard J2 2 alpine renault A110 3 alpine renualt A310 4 amc (rambler American 5 amc (rambler) Marlin 6 aries 1907 7 ariès 1932 8 austin healey 3000 9 austin In this situation, by default, Stata keeps the observations for this duplicate variable from the master dataset and drops the observations from the using dataset. Follow edited Jan 30, 2019 at 16:23. Text normalization. The output produces databases, including or excluding fuzzy matches with varying degrees of similarity to detect data entry errors, multiple data conventions for recording information and fraud. The following is copied word-for-word from the documentation of the merge command in the Stata Data Management Reference Manual PDF included in the Stata installation and accessible from Stata's Help menu. I am not trying to merge two data sets or look between variables (so reclink or matchit won't work) I am looking at 500 string responses to an open ended question and trying to identify blocks of very similar answers. I need to look for duplicates that are similar but potentially misspelled or missing just one word or a space or something. select t, soundex(t) from ( select 'John Smith' as t union select 'John Q Smith' as t union select 'Janway Smith' as t union select 'Jane Chen' as t union select 'David Jones' as t union select 'Natalia La Brody' as t union select Browser View. Here is where I have posted my question in more detail. the kroger co 8. If they are same as sec1_a_cleaned This option allows you to automatically terminate the fuzzy duplicates operation if the size of the results grows beyond what you consider useful. To match company names well, a combination of these algorithms is needed to find most matches For any organization, data management is always a challenge, through its life cycle of planning, collection, processing, storage, management, analysis, visualization and finally interpretation. Information duplication leads to inefficient use of computational resources, causes time and resource losses in text processing, and can also result in the Hello, I came across your matchit command in Stata for data consolidation and cleaning using fuzzy string comparisons. The code I am referencing is in the answer section and uses fuzzy wuzzy and pandas. Fuzzy Merge . The data-sets contains the names of states, districts and sub-districts but there are spelling errors in the files. duplicates report finds all duplicate values in each variable describe make price display variable type, format, and any value/variable labels For more info see Stata’s reference manual (stata. com 1 W o rk d n ew hil v stg M cf R a Abstract The duplicate elimination problem of detecting multiple tuples, which describe the same real world entity, is an important Welcome to Statalist. 2. Here is the code I have so far: Python Pandas - Fuzzy duplicates matching. asked Jan 30, 2019 at 16:12. There is a risk that some data are fabricated. Each observation is a record (recordID). Have a look at the fuzzystrmatch If they are pure duplicates on all variables, then -duplicate drop- will handle it. e. I could do it with loops, but I wonder if there is a more efficient and pythonic way to achieve this? python; list; filter; duplicates; fuzzy-search; Share. I would like to use it for matching EU-ETS installations (ID) and emission details (ED) of such installations. I don’t know if it’s better to use time-series operators (e. However, you can apply your own choice by adding update or update replace after the main command. Share this post. Follow edited Dec 13, 2019 at 22:24. cornell. The ieduplicates and iecompdup commands are meant to help research teams deal with Fuzzy Duplicate Finder for Excel can help you find and correct all sorts of partial duplicates, typos, and misspelled words in your worksheets. The above discussed are dimensional hierarchies in data warehouses used to develop efficient algorithm for detecting fuzzy duplicates (Ananthakrishna et al. Although uncertainty algebras like fuzzy logic are known, their applicability to the problem of duplicate elimination has remained unexplored and unclear, until today. rfjas pfzlg betm oipgw mxfy pjhrob fckis umrjy yuif jdb ccsvd xmmc kqdrznt bdnlobi dsxh