Your Horoscope Matching is depends on your name and date of birth. If you want to check your horoscope using your name contact us Rashi according to alphabet of the name is used during marriage, changing the city or for some other occasions. This is not authentic but people doing it. Some people ask on internet that match our horoscope according to our name and many fake astrologers do it for making lots of money. Know your Zodiac Sign & First letter. If you want to know your Rashi or Zodiac Sign refer to the horoscope and see moon is placed in which number in Ascendant or Lagna Chart. The table below will definitely help. Rashi. Aries. Taurus.
Each block is a syllable. Thick black border indicates stress/emphasis. Other pronunciations are acceptable. Arabic Spelling (How to write Rashid in Arabic) راشد Quranic Nature () Indirectly Mentioned Alternate spellings of Rashid Raachid Rachiyd Raacheyd Raachede Rachid Rashide Raashyde Raashiyd Raashiyd Raachyde Raacheyd Meaning of Rashid Rashid is an indirect Quranic name for boys that means well-guided, wise, mature.
Is derived from the R-Sh-D root which is used in many places in the Quran and is the root for Allah’s name of al-Rasheed. and know that the Messenger of God is among you.
If he were to obey you in many things, you would suffer for it. However, God has endeared the faith to you, and beautified it in your hearts, and has made denial of the truth, wickedness, and disobedience hateful to you. People such as these are rightly guided. (Quran 49:7) The believing man said, “My people, follow me and I shall show you the right guidance… (Quran 40:38) Most Popular Muslim Names in 2018 • 423 views • 388 views • 250 views • 238 views • 235 views • 233 views • 225 views • 222 views • 216 views • 207 views • 207 views • 206 views • 205 views • 200 views • 200 views • 197 views • 197 views • 194 views • 190 views • 189 views • 183 views • 181 views • 178 views • 178 views • 175 views • 175 views • 175 views • 173 views • 168 views • 168 views • 167 views • 164 views • 164 views • 160 views • 159 views • 158 views • 153 views • 152 views • 150 views • 136 views • 132 views • 127 views • 126 views • 125 views • 124 views Do you have additional information on the meaning and origins of this name?
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Most Popular Muslim Names in 2018 • 423 views • 388 views • 250 views • 238 views • 235 views • 233 views • 225 views • 222 views • 216 views • 207 views • 207 views • 206 views • 205 views • 200 views • 200 views • 197 views • 197 views • 194 views • 190 views • 189 views • 183 views • 181 views • 178 views • 178 views • 175 views • 175 views • 175 views • 173 views • 168 views • 168 views • 167 views • 164 views • 164 views • 160 views • 159 views • 158 views • 153 views • 152 views • 150 views • 136 views • 132 views • 127 views • 126 views • 125 views • 124 views •
best matchmaking by rashi name - Select Baby Names First Letter Starts By Rashi
Name Matching Algorithms The basics you need to know about fuzzy name matching When identification numbers are not available, names are often used as a unique identifier. Yet, misspellings, aliases, nicknames, transliteration and translation errors bring unique challenges in matching names. Each fuzzy name matching algorithm excels at solving one or several of these challenges in their own unique ways to provide better matching.
Learn the basics of fuzzy name matching techniques and find out the one that suits you best. What is fuzzy name matching? Fuzzy matching assigns a probability to a match between 0.0 and 1.0 based on linguistic and statistical methods instead of just choosing either 1 (true) or 0 (false).
As a result, names Robert and Bob can be a match with high probability even though they’re not identical. What does “precision” and “recall” mean? Precision: The number of correct results over the total number of results retrieved. High precision indicates the measure of quality.* Recall: The number of correct items you found over the total number of correct items. High recall indicates the measure of quantity.* Pros: Matches across languages and scripts; offers greater precision Cons: Slower performance; high barrier to entry as it requires training data and adjusting features etc.
A statistical approach takes hundreds, if not thousands, of matching name pairs and trains a model to recognize what two “similar names” look like so that the model can take two names and assign a similarity score. A statistical model that has been trained on thousands of pairs of matching names offers high accuracy and the ability to directly match names written in different languages without first transliterating names to Latin script.
This method has a higher barrier to entry, as collecting the matching names requires significant resources, but the accuracy may be well worth the effort. A downside is the slowness of execution. A system only using the statistical method to sift through millions of names to look for matches may be too slow to be feasible in high-transaction environments. Pros: Fast execution, high recall Cons: Mostly limited to Latin-based languages; transliterating non-Latin names reduces precision These methods reduce names to a key or code based on their English pronunciation, such that similar sounding names share the same key.
A well-known common key method is Soundex, patented in 1918. For example, Cyndi, Canada, Candy, Canty, Chant, Condie share the code C530. Many methods take a similar approach to Soundex, including Metaphone and Double Metaphone. These methods use phonetic algorithms which turn similar sounding names into the same key, thus identifying similar names.
Metaphone expands on Soundex with a wider set of English pronunciation rules and allowing for varying lengths of keys, whereas Soundex uses a fixed-length key. Double Metaphone further refines the matching by returning both a “primary” and “secondary” code for each name, allowing for greater ambiguity. In addition, instead of being tied to English pronunciation of characters, it attempts to encompass pronunciations of other origins such as Slavic, Germanic, Celtic, Greek, French, Italian, Spanish, and Chinese.
For example, Double Metaphone encodes “Smith” with a primary code of SM0 and a secondary code of XMT, while it tags “Schmidt” with a primary code of XMT and a secondary code of SMT. That the names share a primary and secondary code of XMT indicates a degree of similarity between the names which Soundex perhaps overstates and which Metaphone misses. Name Metaphone Key Smith SM0 Schmidt SXMTT While the common key method is fast to execute and has good recall, the precision suffers.
Manual inspection of a few names reveals the precision issues. These names share the Soundex key H245: Haugland, Hagelin, Haslam, Heislen, Heslin, Hicklin, Highland, Hoagland. Name Metaphone Key Haugland HKLNT Hagelin HJLN Haslam HSLM Heislen HSLN Heslin HSLN Hicklin HKLN Highland HFLNT Hoagland HKLNT For cases where name similarity is being scored against pairs of names in different scripts—for example Korean hangul vs.
English—the name must first be converted to Latin characters, which potentially introduces more errors to the comparison. Particularly in languages such as Japanese where one character can have more than one correct pronunciations, converting first to the Latin script can introduce fatal mistakes.
The common Japanese female name 洋子 can be correctly pronounced Yoko or Hiroko. Transliteration of names (a mapping of characters or sounds in one script to another) produces many possible variations since sounds in one language have to be approximated.
Variations introduced by transliteration increases the complexity of the already difficult task of matching names. If الرشید عبد is being evaluated against Abdal-Rachid, but the transliteration of الرشید عبد produces Ar-Rashid, will the names come back as a match—as they should?
Name Soundex Key Metaphone Key Abdal-Rachid A134 ABTLRXT Ar-Rashid A623 ARRXT One common key method, the Beider-Morse Phonetic Matching algorithm, does accept Russian in Cyrillic script and Hebrew in Hebrew script, but is otherwise Latin-bound. Pros: Easy to maintain Cons: Computationally intensive (read: expensive hardware needed to run against long lists of names quickly); Cannot handle names the system doesn’t know about; Cannot handle names with missing/added spaces between components; Cannot handle names split between different fields This method attempts to list all possible spelling variations of each name component and then looks for matching names from these lists of name variations.
For example: One system produced 3,024 possible transliterations of this Arabic name “الرشید عبد“ since each separate name component alone has several variations. Here are the first five and last five variations. Trying to generate every possible name variation has a couple of obvious drawbacks.
Name variations which are not in the list will not be found as matches, and perhaps an even greater issue is that of speed and size. Since multi-part names–particularly non-English names–generate an exponentially growing list of variations, searching through these lists takes time.
Given a name with just three components and 20 possible variations per name, the number of possibilities is 203 (=8,000), a very large search space for just one name, now multiply it by the number of names on a watch list! There are further challenges with the list method – how do you score matches when one of your 8,000 query variants matches more than one name in the database?
It is also difficult to handle other types of variation, like nicknames, initials, and titles, without expanding the search space even more. A benefit of the list method is that it is simple to maintain.
When a user complains about a missed match, it’s easily added to the name database. However, easy maintenance may not be enough to offset the decreased speed. For applications with that require high-throughput over millions of names, such as watchlist screening, anti-money laundering (AML), and know your customer (KYC), this approach is likely to be too slow or require a lot of expensive hardware.
Pros: Easy to implement Cons: Limited to Latin-based languages; all swaps are weighted evenly, missing linguistic nuances This approach looks at how many character changes it takes to get from one name to another. “Cindy” and “Cyndi” have an edit distance of 1 since the “i” and “y” are merely transposed, whereas “Catherine” and “Katharine” have an edit distance of 2 as the “C” turns into a “K” and the first “e” becomes an “a.” Methods which look at the character-by-character distance between two names include the Levenshtein distance, the Jaro–Winkler distance, and the Jaccard similarity coefficient.
These approaches look at some combination of two factors (1) the number of similar characters and (2) the number of edit operations it takes to turn one name into the other—the operations being, insert, delete, and transpose.
Although these comparisons are quick, they do not capture linguistic nuance. All edits are given the same weight. Thus changing “c” to “p” is weighted equally as “c” to “k” although in English the latter substitution might more clearly indicate a similar name, as in “Catherine” vs. “Katherine.” Further, a one-to-many character mapping is not possible, as in the case of the Arabic character “sheen” ش which is frequently mapped to “sh” in English. And, just as with the common key method, a non-Latin script name must first be transliterated to Latin script before the comparison can be executed, as explained in the discussion of “The Weakness of the Common Key Method in Matching Across Scripts”.
Pros: makes semantic matches that a spelling-centric method would miss Cons: only relevant to organization name matching Organization names differ from human names in that variations may include synonyms that look and sound entirely different than the target name. In these cases, two names referring to one company are semantically similar but phonetically different. For example, a human can quickly infer that corporation, company, and group are all similar words often found in an organization’s name, but standard name matching techniques like the edit distance method would be unlikely to make the connection.
In these cases, word embeddings can make the match. Word embeddings are numerical vector representations of a word’s semantic meaning. If two words or documents have a similar embedding, they are semantically similar. For example, the embeddings of “woman” and “girl” are close to one another in the vector space, meaning they are semantically similar. Contrastingly, the embeddings of “whale” and “philosophy” are far from one another because they are not semantically related. Applied to organizations, the word embedding method recognizes that Eagle Drugs and Eagle Pharmaceuticals are most likely the same company.
Benefits of Rosette Name Matching • Matches names of people, locations, and organizations • Ranks results by the relevancy based on the confidence score • Matches names regardless of how the names are written in fifteen languages • Leverages cross-script and cross-lingual matching • Takes advantage of semantic similarity algorithms • Provides greater accuracy and recall • Faster and more reliable than legacy solutions • Available to deploy on-premise and on the Cloud API Rosette understands the linguistic complexities of names across fifteen languages.
Contact us today to learn more about the sophistication of Rosette’s name matching algorithm and what difference it could make in your business.
For the Pakistani Test cricketer, see . Rashid Khan Arman (: راشد خان ارمان; born 20 September 1998), commonly known as Rashid Khan, is an Afghan who represents the .
He was one of the eleven cricketers to play in Afghanistan's first ever , against , in June 2018. He also returned the most expensive bowling figures by a debutant in a nation's maiden Test match. Rashid Khan Personal information Full name Rashid Khan Arman Born ( 1998-09-20) 20 September 1998 (age 20) , Afghanistan Batting Right-handed Bowling Right-arm Role International information National side • (2015–present) Only Test (cap ) 14 June 2018 v debut (cap ) 18 October 2015 v Last ODI 25 September 2018 v T20I debut (cap ) 1 October 2016 v Last T20I 22 August 2018 v Domestic team information Years Team 2016–present 2017–present 2017–present 2017–present 2017–present 2018–present 2018–present 2018–present 2018–present Career statistics Competition Matches 52 35 54 134 Runs scored 676 116 697 463 21.80 12.88 21.78 13.22 100s/50s 0/3 0/0 0/3 0/1 Top score 60* 33 60* 56* bowled 2623 792 2730 3089 118 64 122 200 14.47 12.40 14.72 15.65 5 wickets in 4 1 4 4 10 wickets in match n/a n/a n/a n/a Best bowling 7/18 5/3 7/18 5/3 Catches/ 17/– 11/– 18/– 39/– Source: , 15 November 2018 Rashid played in the for .
In June 2017, he took the best bowling figures for an associate nation in a (ODI) match. In February 2018, he became the youngest player to top the for bowlers in ODIs.
Later the same month, he also topped the ICC Player Rankings for bowlers in (T20Is). In September 2018, he became the number one player in the ICC's rankings, following his performance at the . In March 2018, during the , he for the first time in an ODI match. At the age of 19 years and 165 days, he became the youngest player to captain an international side.
In the final of the Cricket World Cup Qualifier, against the , Khan became the fastest and youngest bowler to take 100 wickets in ODIs when he dismissed . He took 44 matches to take his 100th dismissal, breaking the previous record of 52 matches, set by of Australia. In June 2018, he became the fastest bowler, in terms of time, to take 50 wickets in T20Is. He reached the milestone in two years and 220 days, in the first T20I . Rashid Khan was born in 1998 in , eastern Afghanistan.
He hails from , and has ten siblings. When he was still young, his family fled the and lived in for "a few years". They later returned to Afghanistan, resuming their normal life and Rashid continued his schooling. Rashid grew up playing cricket with his brothers and idolised Pakistani all-rounder , from whom he stylised his bowling action.
On 7 December 2016 he made his debut for Afghanistan against in , taking 4 for 48 and 8 for 74, and scoring 25 and 52. Indian Premier League In February 2017, he was bought by for the (IPL) for 4 . He was also amongst the two first ever Afghan players to be selected for the IPL.
He made his IPL debut in the opening fixture of the 2017 tournament, taking two wickets, as the Sunrisers Hyderabad won the match by 35 runs. He finished the tournament as the sixth-highest wicket-taker with 17 wickets from 14 matches. On 5 May 2018, during the , Khan played in his 100th Twenty20 match. He took two wickets, affected a , and was named the man of the match.
Caribbean Premier League A month after getting selected in the IPL, he was bought by for $60,000 to play in the (CPL). In September 2017, he took a for Guyana Amazon Warriors, the first hat-trick in the history of the CPL.
Big Bash League In September 2017, he signed with to play in the , he later went on to win the 2017–18 Big Bash League. In November 2017, he was selected to play for the in . In January 2018, he was bought by the in the . The following month, he was signed by to play in the in England.
Afghanistan Premier League In September 2018, he was named as the Icon Player for 's squad in the of the tournament.
Despite being on the losing side in the final, he was named as the player of the tournament. Other tournaments In October 2018, the (PSL) drafts revealed that Rashid Khan was included in the 14-men Platinum Category.
Later the same month, he was named in 's squad for the of the T20 tournament. He made his (ODI) debut for on 18 October 2015. He made his (T20I) debut, also against Zimbabwe, on 26 October. On 10 March 2017, Khan took his maiden at the second T20I . His figures of five wickets for three runs is the best bowling performance by an Afghan cricket in a T20I and the joint fourth-best figures in all T20Is.
He became the first player to take a five-wicket haul in two overs in a T20I match. Afghanistan won the match and Rashid and shared the man of the match award.
In the , along with , they became the first pair of bowlers from different teams to each take six wickets in the same ODI. On 9 June, he took his second ODI five-wicket haul, finishing with figures of 7 wickets for 18 runs at . It was the fourth best ODI bowling figures and first by an associate nation cricketer to take 7 wickets. Afghanistan defended its total of 212 runs and won the match by 63 runs, and Khan was adjudged man of the match. In January 2018, the (ICC) named him as the Associate Cricketer of the Year.
The following month, he was named as the stand-in captain of the Afghanistan team for the tournament, while Afghanistan's regular captain, , recovered from having his appendix removed.
In February 2018, the ICC named Khan as one of the ten players to watch ahead of the 2018 Cricket World Cup Qualifier tournament. In April 2018, he was named in the squad for the against the , which was played at on 31 May 2018. Test cricket In May 2018, he was named in Afghanistan's squad for their inaugural , played .
He made his Test debut for Afghanistan, against India, on 14 June 2018. On his Test debut he conceded 154 runs in the first innings of the match, becoming the first bowler to concede more than 150 runs in their inaugural Test appearance of any player's country. Rashid's figures of 2 for 154 in the first innings was also the highest number of runs conceded by a bowler in country's inaugural Test match, beating the previous record held by , who conceded 134 runs during Pakistan's debut Test against India in 1952.
During the Afghanistan's inaugural test match he along with set a new record for becoming the first pair of teenagers to concede more than 100 runs each in nation's inaugural Test match. • . ESPN Cricinfo . Retrieved 18 October 2015. • ^ . CricTracker. 15 June 2018 . Retrieved 15 June 2018. • . BBS Sports . Retrieved 9 June 2017. • ^ . Hindustan Times . Retrieved 9 June 2017. • . International Cricket Council . Retrieved 20 February 2018. • . International Cricket Council . Retrieved 25 February 2018.
• . International Cricket Council . Retrieved 30 September 2018. • . International Cricket Council . Retrieved 4 March 2018. • ^ . India Today . Retrieved 25 March 2018. • . ESPN Cricinfo . Retrieved 3 June 2018. • ^ Menon, Vishal (7 April 2017). . Indian Express . Retrieved 9 April 2017.
• ^ Khan, Rashid (2 February 2018). . Players' Voice . Retrieved 3 February 2018. • Isam, Mohammad (27 September 2016). . Cricinfo . Retrieved 5 April 2017. • Penna, Peter Della (5 April 2017). . Cricinfo . Retrieved 5 April 2017. He builds pressure not just through dot balls but through his rapid approach to the crease and quickness through the air, bowling at a pace akin to his idol Shahid Afridi. • Samyal, Sanjjeev K. (21 February 2017).
. Hindustan Times . Retrieved 5 April 2017. I always liked watching leg-break bowlers and Shahid Afridi was my favourite. • . ESPN Cricinfo . Retrieved 8 December 2016. • . ESPN Cricinfo . Retrieved 20 February 2017. • . ESPN Cricinfo . Retrieved 20 February 2017.
• . News18. 20 February 2017 . Retrieved 17 March 2017. • . ESPN Cricinfo . Retrieved 6 April 2017. • . ESPN Cricinfo . Retrieved 7 May 2018.
• . International Cricket Council . Retrieved 7 May 2018. • . ESPN Cricinfo . Retrieved 11 March 2017. • . ESPN Cricinfo . Retrieved 7 September 2017. • . ESPNcricinfo . Retrieved 19 January 2018.
• . BBC Sport. 4 February 2018 . Retrieved 5 February 2018. • . ESPN Cricinfo . Retrieved 13 November 2017. • . ESPN Cricinfo .
Retrieved 27 January 2018. • . BBC Sport . Retrieved 6 February 2018. • . CricTracker . Retrieved 10 September 2018. • . ESPN Cricinfo . Retrieved 22 October 2018. • . • . Sport24 . Retrieved 17 October 2018.
• . Independent Online . Retrieved 17 October 2018. • . ESPN Cricinfo . Retrieved 18 October 2015. • . ESPN Cricinfo . Retrieved 26 October 2015. • . ESPN Cricinfo . Retrieved 10 March 2017. • . ESPN Cricinfo . Retrieved 10 March 2017. • . ESPN Cricinfo . Retrieved 10 March 2017. • . Cricinfo . Retrieved 1 August 2017. • . ESPN Cricinfo . Retrieved 9 June 2017.
• . ESPN Cricinfo . Retrieved 9 June 2017. • . ESPN Cricinfo . Retrieved 9 June 2017. • . International Cricket Council . Retrieved 18 January 2018. • . ESPN Cricinfo . Retrieved 26 February 2018. • . International Cricket Council. 27 February 2018 . Retrieved 27 February 2018. • . International Cricket Council . Retrieved 23 April 2018. • . Afghanistan Cricket Board . Retrieved 29 May 2018. • . ESPN Cricinfo . Retrieved 29 May 2018.
• . ESPN Cricinfo . Retrieved 14 June 2018. • . CatchNews.com . Retrieved 15 June 2018. • Staff, CricketCountry (15 June 2018). . Cricket Country . Retrieved 15 June 2018.
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