Can i rank my website keywords in 1 month ?

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I’d like to create a Smart Collection to include those which have certain keywords and exclude all other keywords

I have marked my photos using keywords of the names of people, say A B C D & E and so on. I want to use smart collections to trap all photos where there are keywords A AND B. However, this traps even those where C and/or D and/or E and/or others may be in the photo. I can write individual conditions to exclude C D & E, but since I have about 100 keywords, this would make the number of excluding conditions too long.

Is there a way where I can trap only keywords A AND B and exclude all other keywords more conveniently than writing individual exclusions?

Keywords dropped by 50 positions.

Hey. I know that google is solving canonical tag issue. Today ive checked my seobility account and i was shocked. 50 position drop for few keywords who points to same page. There is many pages with canonical tag to page with rating issue so assume its the same problem. All those keywords few days ago was stable 1-3 place. There is no errors in webmasters.

So my question is, should i just chill and wait till their fix it or? Resubmit everything or even redirect instead of canonical?

keywords – Online Database – Webmasters Stack Exchange

Is it possible to to make data base and save in computer as below?

I want make searchable database ( search keyword from ) on my windows 10, which is available in word format in online website. Approximately 1000pages +.
Thanks in advance.

python – Substring match within a text for given keywords

Goal:

Look for a substring match within a text for given Keywords. Keep the substring match if the levenshtein distance is smaller than the length of the Keyword divided by (x=10), else return an empty list.

(First of all my apologies if the code is of lower quality. I am quite good in R but very new to Python.)

Current implementation:

from fuzzywuzzy import process
from fuzzysearch import find_near_matches
import math

def fuzzy_extract(qs, ls, threshold, max_dist):
    ret = ()
    for word, _ in process.extractBests(qs, (ls,), score_cutoff = threshold):
        for match in find_near_matches(qs, word, max_l_dist = max_dist):
            word = word(match.start:match.end)
            ret.append({"kw": qs, "word": word, "dist": match.dist})
    return(ret)

def get_match(text, keywords, treshold):
    keywords = (keyword.lower() for keyword in keywords)
    text = text.lower()
    
    candidates = ()
    for li in (fuzzy_extract(query_string, text, 0, 1) for query_string in keywords):
        if len(li) > 0:
            for di in li:
                if di("dist") <= math.ceil(len(di("word"))/treshold):
                    candidates.append(di)
    
    if(len(candidates) == 0):
        return(())

    out = str(candidates(0)("kw"))
    return(out)

keywords = ("apple", "banana", "cherry")
text = "nana is Looking for an aple."

print(get_match(text, keywords, 10))

For me the part in the middle looks neither efficient and also not very declarative.
With part in the middle i mean the Code following:

for li in (fuzzy_extract(query_string, text, 0, 1) for query_string in keywords):

I started with something longer but more declarative:

candidates = (fuzzy_extract(query_string, ocr_text, 0, 1) for query_string in keywords_ordering)
lens = (len(candidate) > 0 for candidate in candidates)
candidate_lengths = list(compress(candidates, lens))
filtered = (candidate_length(0)("dist") < math.ceil(len(candidate_length(0)("word"))/10) for candidate_length in candidate_lengths) 
candidate_filtered = list(compress(candidate_lengths, filtered))

In R i would make usage of pipes for These cases to avoid the undeclarative variables in between.

Similar Topics:

Find a best fuzzy match for a string

(Difference is that in this question match candidates are compared to a single word and to a substring of a text).

https://stackoverflow.com/a/36132391/3502164

Custom implementation, rather long.

Casino, Poker, Agen judi bola, Sport, Betting, all Gambling sites – Google Rank 100 -150 Keywords for $250

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file management – How to find photos that do not have any keywords assigned to them in Adobe Bridge?

I’m trying to organize my archive using Adobe Bridge. In one step I messed and moved some untagged photos to another folder that all its photos are already tagged. These photos are parts of my everyday street photography photos, so they are taken on different days and can not be distinguished visually.

Is it possible to filter photos that do not have any keywords assigned to them in Adobe Bridge?

I searched the web and couldn’t find anything. Perhaps I’m missing the right keywords.
Thanks in advance for your help.

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