गूगल रैंकिंग सिग्नल्स क्या है? | List of Google Ranking Signals | Google Ranking Factors

अगर आपके पास किसी भी तरह की वेबसाइट है तो Google Ranking Signals या Google Search Ranking Systems के बारे में समझना होगा। यहाँ हमने इसको विस्तार से समझाया है। साथ ही List of Google Ranking Signals और Google Ranking Factors की जानकारी भी दी है।

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Google Search Ranking Systems क्या है?

Google Search Ranking Systems se matlab hota hai Google ke complex algorithms aur processes se, jinki madad se web pages ko search engine results pages (SERPs) me kis order me display karna hai specific queries ke liye. Google ke search ranking systems ka maksad users ko unke search queries ke basis par sabse relevant aur high-quality results provide karna hota hai.

Google ke ranking systems ki sahi jaankariyan proprietary hoti hai aur hamesha evolve hoti rehti hai, lekin generally ye sadiyon ke factors aur signals ka mishran hai, jinhone web pages ki relevance, authority aur user experience ka mulyankan kiya hai. Kuch key components aur considerations of Google’s ranking systems include karte hain:

Google’s ranking systems key components

1. Relevance: Google search queries ko sabse relevant web pages ke saath match karne ki koshish karta hai. Ye various on-page factors jaise keywords, content quality aur search terms ke saath relevance jaise cheezein evaluate karta hai.
2. Backlinks: Google ek web page ki authority aur popularity ka indicator maanta hai uske paas jin websites se links aate hain, unki quantity aur quality. Reputable websites se high-quality backlinks ka presence ek page ke ranking ko positively influence kar sakta hai.
3. User Experience: Google user experience signals par importance deta hai, jaise page load speed, mobile-friendliness aur navigation ki aasaani. Websites jo positive user experience provide karte hain, unka ranking higher hota hai.
4. Content Quality: Google ko priority hai high-quality, original aur informative content wale pages ko. Readability, relevance aur content ki depth jaise factors ko consider kiya jata hai page ki quality ka mulyankan karte samay.
5. User Engagement: User engagement ke indicators jaise click-through rates (CTRs), bounce rates aur dwell time (users ka page par bitaya gaya time) rankings par asar dal sakte hain. Pages jo users ko engage karte hain aur unki needs ko pura karte hain, unka ranking accha hota hai.
6. Search Intent: Google user ke search query ke peeche ke intent ko samajhna chahta hai aur results provide karna chahta hai jo us intent se match karte hain. Pages jo effectively user ke query ko address karte hain aur relevant information provide karte hain, unka ranking higher hota hai.
7. Localization: Location-based searches ke liye, Google user ke geographical location ko consider karta hai aur results provide karta hai jo unki location ke relevant hote hain.

Google Ranking Signals

Google apne automated ranking systems ka istemal karta hai jo hazaaron arab web pages aur doosre content ke baare mein bahut saare factors aur signals ko dekhta hai, jo unke search index mein hote hain, taki ve sabse relevant aur upyogi results ko ek second ke ansh mein prastut kar sake.

Google niyamit roop se system mein sudhaar karte hain, kathor parikshan aur mulyankan jaari rakhte hain aur ye update ke notices dete hain apne ranking system ke baare mein jab wo content nirmaata aur doosre logon ke liye upyogi ho sakte hain.

Ye page ek guide hai kuch prasiddh Google ranking systems ko samajhne ke liye. Isme hum kuch aise systems ko cover kar rahe hain jo Google core ranking system ka hissa hai. Ismein vishisht ranking ki zaroorat ke saath-saath kuch systems ko bhi cover kiya gaya hai.

Google ka commitment duniya ki jankari ko vyavasthit karna aur ise sarvatra upyogi aur pahuchne layak banana ke liye ek advanced network of ranking systems dwara sambhav hai. Ye systems hamesha rigorous testing aur evaluation ke tahat se guzarte rehte hain taki unki effectiveness high-quality search results prastut karne mein sahi rahe.

Understanding Google’s Core Ranking Systems

1. BERT: Bidirectional Encoder Representations from Transformers

BERT, jo ki Bidirectional Encoder Representations from Transformers ka short form hai, ek artificial intelligence system hai jo Google dwara istemaal kiya jata hai. BERT Google ki kshamata ko badhata hai ki kaise shabdo ke combinations alag-alag meanings aur intentions ko convey karte hain. User queries ke context aur nuances ko samajhkar, BERT Google ki madad karta hai ki wah sahi aur relevant search results prastut kar sake.

2. Crisis Information Systems

Vyaktigat ya vyapak sankat ke samay, Google ke crisis information systems samay par sahayak aur upyogi jankari pradan karna mein mahatvapurna bhumika nibhate hain. Ye systems vyaktiyo dwara vyaktigat sankat se sambandhit jankari ki khoj karne par dhyan dena ki design kiye gaye hote hain, jaise ki suicide, sexual assault ya drug addiction. Google trusted organizations ke hotlines aur content ko aise queries ke liye display karta hai. Iske alawa, SOS Alerts system ke madhyam se, Google prakritik apda ya sankat ki sthiti mein sthanik, rashtriya ya antarrashtriya adhikarikyon se aane wale updates ko dikhata hai.

3. Deduplication Systems

Google ke deduplication systems search results mein ek doosre se bilkul same ya bahut similar web pages ko display karne ki samasya ko handle karte hain. Behtar user experience aur sahi jankari ki khoj ko facilitate karne ke liye, ye systems sabse relevant results ko priority dete hain aur anukool duplication ko rokte hain. Usi tarah, featured snippets ke liye, agar ek web page ka listing featured snippet ke roop mein promote kiya gaya hai, to woh baad mein first page ke results mein dobara repeat nahi hoga, jisse user experience streamline hota hai aur upayukt jankari ki khoj ko aasan banaya jata hai.

4. Exact Match Domain System

Google ke exact match domain system se dhyan rakha jaata hai ki kisi vishesh query ke sath milne ke liye tayyar kiye gaye domain names ko zyada ranking credit na diya jaye. Is system se rankings adjust kiye jaate hain taaki sirf ranking ke uddeshya se banaye gaye domain names ke neeche host ki gayi content ko anuchit fayda na mile.

5. Freshness Systems

Google ke “query deserves freshness” systems ka lakshya hai ki aise queries ke liye hamesha fresh content uplabdh karaya jaaye jahan haal hi mein hone wali ghatna ya taaza hone ki zaroorat hoti hai. Jaise ki agar istemal karne wale log haal hi mein release hui ek film ke baare mein search karte hain, to unhe purane articles ke bajaye haal hi mein likhi gayi taaza reviews zyada milte hain. Usi tarah, zameen ke jhatke jaise aapda ke waqt, search results mein khabar articles aur abhi ke samay mein hone wali jaankari ko pehle dikhaya jaata hai.

6. Helpful Content System

The helpful content system by Google aims to give priority to original and informative content that is created by individuals for the benefit of others. It focuses on displaying content that provides valuable insights, expert analysis, and genuine user experiences. The goal is to ensure that search results are driven by quality and relevance, rather than solely relying on search engine optimization strategies. This system encourages the creation of high-quality content that genuinely helps users find the information they are looking for.

7. Link Analysis Systems and PageRank

Google’s link analysis systems examine how web pages interconnect through links, helping determine the content’s subject matter and its usefulness in response to user queries. One of the fundamental ranking systems, PageRank, was initially employed by Google during its early days. Over time, PageRank has evolved, and it continues to play a crucial role in Google’s core ranking systems.

8. Local News Systems

To provide users with relevant local news, Google has dedicated systems that identify and highlight local news sources. These systems contribute to features like “Top stories” and “Local news,” ensuring users receive localized information that matters to them.

9. MUM: Advancing Language Understanding

MUM, which stands for Multitask Unified Model, is an AI system capable of both comprehending and generating language. Although MUM is not currently used for general ranking in Search, it serves specific applications such as improving searches for COVID-19 vaccine information and enhancing featured snippet callouts.

10. Neural Matching

Neural matching is an AI system implemented by Google to comprehend the representations of concepts within queries and web pages. By matching these representations, Google improves the accuracy of search results, connecting users with the most relevant information.

11. Original Content Systems

Google’s original content systems are designed to prioritize prominently displaying original content in search results. This includes original reporting and authoritative sources, allowing users to access the primary information source efficiently.

12. Removal-Based Demotion Systems

To address specific types of content that require removal, Google has policies in place. When a high volume of valid copyright removal requests or personal information removals is processed for a particular site, Google utilizes this information to demote other content from the same site in search results. This proactive approach helps safeguard against encountering infringing, defamatory, or exploitative content.

13. Passage Ranking System

Google’s passage ranking system enables the identification and evaluation of individual sections or passages within web pages. This system enhances the understanding of the relevance of specific content sections to user queries, facilitating precise and targeted search results.

14. RankBrain:

RankBrain is an AI system developed by Google to comprehend the relationships between words and concepts. By analyzing the context of search queries and understanding the semantic connections, RankBrain enhances the delivery of relevant content, even if it doesn’t precisely match the exact words used in the search.

15. Reliable Information Systems

In its commitment to provide reliable information, Google has implemented various systems that ensure the promotion of authoritative sources and the

demotion of low-quality content. In cases where information quality is uncertain or rapidly changing, Google displays content advisories to guide users in their search and inform them of potential information gaps.

16. Reviews System

The reviews system emphasizes rewarding high-quality reviews that offer insightful analysis, original research, and expert knowledge. By prioritizing these reviews, Google enhances the visibility of valuable user-generated content and helps users make informed decisions.

17. Site Diversity System

To promote diversity in search results, Google’s site diversity system limits the number of web page listings from the same site in the top results. This ensures that no single site dominates the rankings. While subdomains are generally treated as part of the root domain, exceptions are made to address relevant subdomains as separate entities for diversity purposes.

18. Spam Detection Systems

Similar to spam filters in email systems, Google employs spam detection systems to combat spam content and manipulative behaviors. These systems, including SpamBrain, are regularly updated to counter evolving spam techniques and ensure the delivery of helpful and relevant search results.

Retired Systems

Google ne kuch ranking systems ko sanyas diya hai, kyunki ya to unko unke uttaradhikari systems mein samahit kiya gaya hai ya fir unko mool ranking systems mein shamil kar liya gaya hai. Kuch retired systems is tarah se hain:

A. Hummingbird

Hummingbird was a major improvement to Google’s overall ranking systems introduced in August 2013. While it was significant at the time, it has since been superseded by subsequent advancements and is no longer considered a standalone ranking system.

B. Panda System

The Panda system, announced in 2011, aimed to ensure high-quality and original content appeared prominently in search results. Initially introduced as a separate system, it became integrated into Google’s core ranking systems in 2015. Its principles of promoting quality content continue to be incorporated in the current ranking algorithms.

C. Penguin System

The Penguin system, announced in 2012, targeted link spam practices. It aimed to discourage manipulative link-building techniques and promote the use of natural, high-quality links. The Penguin system was later integrated into Google’s core ranking systems in 2016.

Conclusion

Google’s search ranking systems are a testament to the continuous evolution and improvement of technology. The core ranking systems, along with specialized systems for specific needs, enable Google to deliver relevant and useful search results to billions of users worldwide. By understanding these systems, content creators and users alike can gain insights into the mechanisms that shape the search landscape.

Google Ranking Signals Frequently Asked Questions (FAQs)