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B2 noun 9分で読める

داده‌کاوی

例文 داده‌کاوی 30秒で
解説 داده‌کاوی in your Level:
At the A1 level, 'داده‌کاوی' (Data Mining) is a very advanced word. However, you can think of it as 'searching for secrets in information.' Imagine you have a very big book with many numbers. If you look for a pattern in those numbers, you are doing something like 'داده‌کاوی.' At this stage, you don't need to use the word in sentences, but you might see it in a technology magazine. Think of 'داده' (dāde) as 'info' and 'کاوی' (kāvi) as 'looking closely.' It's like being a detective for numbers and facts. Even though it's a long word, it's just two parts put together. In Persian, we often make new words by joining two simple words. If you know 'داده' means data, you are already halfway there! This word helps you realize that Persian is used for very modern things, not just for poetry or daily life. You might hear it on the news when people talk about computers. Just remember: it's about finding things that are hidden in a lot of information.
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At the A2 level, you are starting to learn about professions and technology. 'داده‌کاوی' is the Persian word for 'Data Mining.' You can recognize the word 'داده' which means 'data.' The second part, 'کاوی,' comes from a verb that means 'to dig.' So, it is 'digging in data.' You might use this word if you are talking about your job or what you study at university. For example, 'من داده‌کاوی دوست دارم' (I like data mining). It is a formal word, so you will see it in newspapers or on TV. It’s useful to know because Iran has many computer engineers. If you meet an Iranian who works with computers, they will definitely know this word. You can use it to ask questions like: 'آیا این شرکت داده‌کاوی انجام می‌دهد؟' (Does this company do data mining?). It’s a great word to show that you are learning more than just basic greetings. It helps you talk about the modern world and technology in Persian.
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At the B1 level, you should be able to understand 'داده‌کاوی' in context and use it in simple discussions about technology or business. It is a compound noun. You should know that 'داده‌کاوی' is a process. You use it to find patterns. For example, 'داده‌کاوی به ما کمک می‌کند تا مشتریان را بشناسیم' (Data mining helps us to know the customers). You will notice that in Persian, we use a 'half-space' (نیم‌فاصله) between the two parts. This is important for your writing. You might also encounter related words like 'تحلیل داده' (data analysis). While 'تحلیل' is about analyzing, 'کاوی' is specifically about 'mining' or 'extracting' something new. You can start using this word in your essays about the internet or the future of technology. It’s an essential term for anyone interested in the Iranian job market or academic sphere. Try to use it when explaining how websites recommend movies or products to you; that is all thanks to 'داده‌کاوی.'
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At the B2 level, you are expected to use 'داده‌کاوی' with precision in professional and academic contexts. You should understand that it involves specific algorithms and statistical methods. You should be able to discuss its applications, such as in 'بازاریابی' (marketing), 'پزشکی' (medicine), and 'امنیت' (security). At this level, you should also be familiar with the ezāfe constructions like 'روش‌های داده‌کاوی' (data mining methods) or 'نتایج داده‌کاوی' (data mining results). You should be able to contrast it with other terms like 'یادگیری ماشین' (machine learning) or 'آمارهای توصیفی' (descriptive statistics). Your sentences should become more complex: 'با استفاده از تکنیک‌های پیشرفته داده‌کاوی، می‌توان رفتارهای آتی بازار را پیش‌بینی کرد' (Using advanced data mining techniques, one can predict future market behaviors). You should also be aware of the ethical discussions surrounding data mining, such as 'حریم خصوصی' (privacy). This word is a gateway to high-level technical Persian conversation.
At the C1 level, 'داده‌کاوی' is a word you should be able to use fluently in a variety of registers, especially in formal presentations or academic papers. You should understand its nuances—for example, the difference between 'داده‌کاوی' and 'متن‌کاوی' (text mining) or 'وب‌کاوی' (web mining). You should be able to discuss the history of the term and how it fits into the broader field of 'هوش مصنوعی' (artificial intelligence). At this level, you can use the word to construct sophisticated arguments about the role of big data in modern society. You might say: 'داده‌کاوی نه تنها یک ابزار تجاری، بلکه یک ضرورت راهبردی در مدیریت کلان‌داده‌هاست' (Data mining is not just a business tool, but a strategic necessity in the management of big data). You should also be comfortable with the verbal forms and related phrases like 'کاویدنِ داده‌ها' or 'استخراج الگو'. Your understanding should extend to the specific algorithms used in the Persian academic context, such as 'درخت تصمیم' (decision tree) or 'شبکه‌های عصبی' (neural networks) as they relate to data mining.
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At the C2 level, you have a masterly command of 'داده‌کاوی' and its theoretical underpinnings. You can engage in deep philosophical or technical debates about the limitations and future of data mining. You understand the etymological beauty of the suffix '-kāvi' and how it connects to classical Persian roots while serving modern scientific needs. You can critique Persian translations of international data science standards and suggest improvements. Your usage of the word is indistinguishable from that of a native data science expert. You can discuss 'داده‌کاوی' in the context of 'معرفت‌شناسی' (epistemology)—how we derive knowledge from raw information. You might write: 'پارادایم‌های نوین در داده‌کاوی مرزهای بین استنتاج آماری و هوش ماشینی را کمرنگ کرده‌اند' (Modern paradigms in data mining have blurred the boundaries between statistical inference and machine intelligence). You are also aware of the most recent Persian research papers in this field and can discuss the specific challenges of data mining for the Persian language, such as 'پردازش زبان طبیعی' (NLP) for Farsi scripts.
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例文

داده‌کاوی 30秒で

  • داده‌کاوی به معنای استخراج الگوهای پنهان از داده‌های حجیم است.
  • این واژه از ترکیب 'داده' و 'کاوی' (به معنی جستجو و حفاری) ساخته شده است.
  • در حوزه‌هایی مانند بازاریابی، پزشکی و امنیت کاربرد فراوانی دارد.
  • یک مهارت کلیدی برای متخصصان علوم داده و تحلیلگران در دنیای مدرن محسوب می‌شود.

The term داده‌کاوی (Dāde-kāvi) is a sophisticated compound noun in Persian that translates directly to 'Data Mining.' In the modern digital landscape, it represents the computational process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. The word itself is a blend of داده (dāde), meaning 'data' or 'given,' and کاوی (kāvi), a suffix derived from the verb کاویدن (kāvidan), which means to dig, excavate, probe, or explore deeply. This linguistic construction perfectly mirrors the English concept: just as miners dig through earth to find precious minerals, data scientists 'dig' through mountains of digital information to find 'nuggets' of insight. In Persian-speaking academic and professional circles, particularly in Iran's growing tech hubs like Tehran and Isfahan, this term is ubiquitous. It is used when discussing business intelligence, predictive modeling, and even social media analysis. Understanding this word requires more than just knowing its translation; it requires an appreciation of how Persian adapts to high-tech terminology by utilizing its rich system of roots and suffixes.

Domain
Information Technology and Data Science
Register
Formal, Academic, and Professional
Morphology
Compound: Noun (داده) + Present Stem (کاو) + Nominalizing Suffix (ی)

شرکت‌های بزرگ از داده‌کاوی برای درک بهتر نیازهای مشتریان خود بهره می‌برند.

(Large companies utilize data mining to better understand their customers' needs.)

الگوریتم‌های داده‌کاوی می‌توانند الگوهای پنهان در تراکنش‌های بانکی را شناسایی کنند.

(Data mining algorithms can identify hidden patterns in bank transactions.)

Beyond the technical definition, the word carries a sense of intellectual rigor. It is not just 'looking' at data; it is an active, methodical search. In Persian literature, 'کاویدن' has been used for centuries to describe searching for truth or meaning in philosophical texts. Its modern adaptation into 'داده‌کاوی' shows the continuity of the Persian language. When you use this word, you are signaling that you are part of the modern, educated workforce in the Persian-speaking world. It is a term that bridges the gap between traditional linguistic roots and the cutting edge of global technology. Whether you are discussing the ethics of privacy or the efficiency of a new marketing strategy, this word provides the necessary precision. It’s also important to note that while 'آنالیز داده' (Data Analysis) is more general, 'داده‌کاوی' specifically implies the extraction of previously unknown, valid, and actionable information from massive sets.

Using داده‌کاوی correctly involves understanding its role as a noun that often functions as the subject or object of a sentence. It frequently appears in 'ezāfe' constructions, where it is linked to other nouns to provide more detail. For example, ابزارهای داده‌کاوی (Data mining tools) or متخصص داده‌کاوی (Data mining specialist). Because it is a technical term, the verbs associated with it are often formal, such as انجام دادن (to perform), به کار گرفتن (to employ), or استفاده کردن (to use). In academic writing, you might see it paired with روش (method) or تکنیک (technique). Below are various ways to integrate this word into your vocabulary, ranging from simple descriptions to complex analytical statements.

او پایان‌نامه خود را در زمینه داده‌کاوی در شبکه‌های اجتماعی نوشت.

(He wrote his thesis in the field of data mining in social networks.)

آیا داده‌کاوی می‌تواند به پیش‌بینی تغییرات اقلیمی کمک کند؟

(Can data mining help predict climate changes?)

ما برای بهبود فروش، به یک تیم داده‌کاوی حرفه‌ای نیاز داریم.

(To improve sales, we need a professional data mining team.)

When constructing sentences, remember that 'داده‌کاوی' is an abstract process. You don't 'eat' or 'touch' it; you 'apply' it or 'study' it. If you are describing a person's profession, you would say او در حوزه داده‌کاوی فعالیت می‌کند (He/She works in the field of data mining). If you are discussing the results of the process, you might say نتایج حاصل از داده‌کاوی نشان داد که... (The results obtained from data mining showed that...). This word is also central to discussions about Big Data (داده‌های بزرگ). As you progress in your Persian studies, you will notice that technical terms like this are often used in the same sentence structure as their English counterparts, making it easier for English speakers to grasp the syntax once the vocabulary is mastered. Always ensure that the 'ی' at the end is pronounced clearly as a long 'ee' sound, as it transforms the action into the field of study.

You will encounter داده‌کاوی in several specific environments. First and foremost is the university setting. Iran has a very strong engineering and computer science culture, and courses on 'Data Mining' are standard in many curricula. In these settings, the word is used in lectures, textbooks, and seminars. Secondly, you will hear it in the corporate world, specifically in the 'Tehran-Pars' (a common nickname for the tech sector) and start-up incubators. Managers and developers use it when discussing user behavior, market trends, and optimization. Thirdly, it appears frequently in news reports concerning technology, cybersecurity, and the economy. If a news anchor is talking about how a bank detected fraud or how a health organization tracked a pandemic, 'داده‌کاوی' is the word they will use to describe the analytical process behind it.

Context 1
Academic Lectures and Textbooks on CS and Statistics.
Context 2
Business Meetings and Strategy Planning Sessions.
Context 3
Tech Podcasts and YouTube Channels in Persian.

در این پادکست، ما به بررسی اهمیت داده‌کاوی در هوش مصنوعی می‌پردازیم.

(In this podcast, we examine the importance of data mining in artificial intelligence.)

Furthermore, social media platforms like LinkedIn are filled with Persian-speaking professionals listing 'داده‌کاوی' as one of their core skills. In recruitment, job descriptions for 'تحلیلگر داده' (Data Analyst) almost always require proficiency in 'داده‌کاوی'. You might also hear it in political discourse, where commentators discuss how 'داده‌کاوی' is used to influence voters or analyze census data. Because the word is so specific, it isn't used in casual street slang, but it is a staple of the 'educated urban' dialect. If you are watching a Persian tech review on YouTube, keep your ears open for this word; it is almost guaranteed to appear whenever the reviewer discusses software features or recommendation algorithms. It is a word that signifies the transition of Persian into a language of the information age.

One of the most common mistakes learners make with داده‌کاوی is confusing it with جمع‌آوری داده (Data Collection). While collection is the act of gathering information, 'داده‌کاوی' is the analytical process that happens *after* the data is collected. Another mistake is in the spelling; many beginners forget the 'نیم‌فاصله' (zwnj) and write it as داده کاوی (with a full space) or دادهکاوی (all together). While understandable, the first is technically two separate words and the second is unreadable. In formal writing, the half-space is mandatory. Additionally, learners sometimes use the wrong preposition. You do data mining *on* data, but in Persian, you often say داده‌کاوی روی داده‌ها or داده‌کاوی در مجموعه‌داده‌ها. Using 'با' (with) might be grammatically possible but often sounds less natural in a technical context.

اشتباه: من در حال داده‌کاوی اطلاعات از اینترنت هستم.

(Mistake: I am 'data mining' information from the internet. Correction: Use 'جمع‌آوری' if you are just gathering it.)
Mistake Type
Semantic Confusion: Mixing up analysis with collection.
Mistake Type
Orthographic Error: Incorrect spacing (using full space instead of half-space).

Another subtle error is the mispronunciation of the 'v' sound in 'kāvi'. Some learners might pronounce it more like a 'w' sound, but in modern Persian, it is a distinct 'v' (labiodental fricative). Also, ensure you don't confuse the suffix '-kāvi' with '-kāri' (which means 'work' or 'doing'). 'داده‌کاری' is not a word and would sound very strange to a native speaker. Finally, avoid using 'داده‌کاوی' to describe simple tasks like looking up a phone number or checking a list. It is reserved for complex, algorithmic processes. If the task doesn't involve finding *patterns* or *hidden* information, 'جستجو' (search) or 'بررسی' (investigation) are better choices. By avoiding these pitfalls, your Persian will sound much more professional and technically accurate.

While داده‌کاوی is the standard term for data mining, there are several related terms that you should know to build a complete vocabulary in this domain. تحلیل داده‌ها (Data Analysis) is the most common alternative, though it is broader in scope. هوش تجاری (Business Intelligence) often encompasses data mining but refers to the broader goal of making business decisions. یادگیری ماشین (Machine Learning) is the set of algorithms often used *during* the data mining process. Understanding the nuances between these terms is key to B2-level proficiency. For example, you 'mine' data to 'learn' patterns, which you then 'analyze' to provide 'intelligence'.

داده‌کاوی vs. تحلیل داده
Dāde-kāvi is about discovery of patterns; Tahlil-e dāde is about inspecting and modeling data to support decision-making.
داده‌کاوی vs. متن‌کاوی
Dāde-kāvi is general; Matn-kāvi is specifically the mining of unstructured text data.
داده‌کاوی vs. آمار
Statistics (Āmār) provides the mathematical foundation, but data mining is more focused on the computational application to large datasets.

تفاوت اصلی بین داده‌کاوی و آمار در حجم داده‌ها و اهداف کاربردی آن‌هاست.

(The main difference between data mining and statistics is in the volume of data and their practical goals.)

In some contexts, you might also hear اکتشاف داده‌ها (Data Exploration), which is usually the initial step of looking through data before the actual mining begins. Another related term is انبارش داده‌ها (Data Warehousing), which refers to the storage aspect. If you are working in a specialized field, you might encounter وب‌کاوی (Web Mining) or تصویرکاوی (Image Mining). All these terms share the '-kāvi' suffix, emphasizing the act of deep exploration. By learning this family of words, you can navigate complex technical discussions in Persian with ease. This linguistic pattern is one of the strengths of Persian, allowing for the creation of precise, logical terminology for new scientific frontiers.

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レベル別の例文

1

داده‌کاوی جالب است.

Data mining is interesting.

Simple subject + adjective + verb 'to be'.

2

او داده‌کاوی می‌خواند.

He/She studies data mining.

Subject + object + present continuous verb.

3

کتاب داده‌کاوی کجاست؟

Where is the data mining book?

Noun + ezāfe + noun.

4

داده‌کاوی سخت نیست.

Data mining is not hard.

Negative form of the verb 'to be'.

5

این یک داده‌کاوی است.

This is a data mining (process).

Demonstrative pronoun + indefinite noun.

6

من داده‌کاوی بلد هستم.

I know data mining.

Using 'balad hastam' for knowing a skill.

7

داده‌کاوی در کامپیوتر است.

Data mining is in the computer.

Prepositional phrase.

8

نام این داده‌کاوی است.

The name of this is data mining.

Simple possessive structure.

1

او در شرکت داده‌کاوی کار می‌کند.

He works in a data mining company.

Prepositional phrase with a compound noun.

2

ما به داده‌کاوی نیاز داریم.

We need data mining.

Verb 'niyāz dāštan' (to need) + preposition 'be'.

3

آیا داده‌کاوی برای تجارت خوب است؟

Is data mining good for business?

Question form with 'āyā'.

4

او درس داده‌کاوی را دوست دارد.

He likes the data mining lesson.

Direct object with 'rā'.

5

داده‌کاوی اطلاعات زیادی به ما می‌دهد.

Data mining gives us a lot of information.

Subject + object + indirect object + verb.

6

آن‌ها از داده‌کاوی استفاده می‌کنند.

They use data mining.

Verb 'estefāde kardan' + preposition 'az'.

7

داده‌کاوی الگوها را پیدا می‌کند.

Data mining finds patterns.

Simple present tense with a plural object.

8

این نرم‌افزار برای داده‌کاوی است.

This software is for data mining.

Preposition 'barāye' (for).

1

داده‌کاوی به شرکت‌ها کمک می‌کند تا رفتار مشتری را پیش‌بینی کنند.

Data mining helps companies to predict customer behavior.

Complex sentence with 'tā' (so that/to).

2

بدون داده‌کاوی، تحلیل این همه اطلاعات غیرممکن است.

Without data mining, analyzing all this information is impossible.

Conditional sense using 'bedun-e' (without).

3

او در حال یادگیری الگوریتم‌های مختلف داده‌کاوی است.

He is learning different data mining algorithms.

Present progressive tense.

4

داده‌کاوی می‌تواند الگوهای پنهان را در داده‌های بزرگ کشف کند.

Data mining can discover hidden patterns in big data.

Modal verb 'tavānestan' (can).

5

در این مقاله، اهمیت داده‌کاوی در پزشکی بررسی شده است.

In this article, the importance of data mining in medicine has been examined.

Passive voice in the present perfect tense.

6

بسیاری از بانک‌ها برای تشخیص تقلب از داده‌کاوی بهره می‌برند.

Many banks utilize data mining for fraud detection.

Verb 'bahre bordan' (to utilize/benefit).

7

آیا شما با ابزارهای داده‌کاوی آشنایی دارید؟

Are you familiar with data mining tools?

Adjective 'āšnāyi dāštan' (to have familiarity).

8

داده‌کاوی یکی از شاخه‌های مهم علوم کامپیوتر است.

Data mining is one of the important branches of computer science.

Superlative/Partitive construction 'yaki az'.

1

تکنیک‌های داده‌کاوی به منظور استخراج دانش از پایگاه‌های داده بزرگ به کار می‌روند.

Data mining techniques are employed to extract knowledge from large databases.

Formal passive construction 'be kār raftan'.

2

یکی از چالش‌های اصلی در داده‌کاوی، حفظ حریم خصوصی کاربران است.

One of the main challenges in data mining is maintaining user privacy.

Complex subject with an infinitive 'hefz' (maintaining).

3

داده‌کاوی در بازاریابی به شناسایی گروه‌های هدف کمک شایانی می‌کند.

Data mining in marketing significantly helps in identifying target groups.

Use of 'šāyāni' (significant) to modify the help given.

4

متخصصان داده‌کاوی باید با زبان‌های برنامه‌نویسی مانند پایتون آشنا باشند.

Data mining specialists must be familiar with programming languages such as Python.

Subjunctive mood with 'bāyad' (must).

5

فرآیند داده‌کاوی شامل مراحل پیش‌پردازش، مدل‌سازی و ارزیابی است.

The data mining process includes preprocessing, modeling, and evaluation stages.

Verb 'šāmel budan' (to include).

6

داده‌کاوی می‌تواند به بهبود سیستم‌های توصیه‌گر در وب‌سایت‌های فروشگاهی کمک کند.

Data mining can help improve recommendation systems on e-commerce websites.

Compound noun 'system-hā-ye tosiye-gar'.

7

نتایج حاصل از داده‌کاوی باید به درستی توسط مدیران تفسیر شوند.

The results obtained from data mining must be correctly interpreted by managers.

Passive voice with 'tavasot-e' (by).

8

در عصر کنونی، داده‌کاوی ابزاری حیاتی برای تصمیم‌گیری‌های استراتژیک است.

In the current era, data mining is a vital tool for strategic decision-making.

Abstract academic register.

1

داده‌کاوی به عنوان پلی میان آمار کلاسیک و هوش مصنوعی نوین عمل می‌کند.

Data mining acts as a bridge between classical statistics and modern artificial intelligence.

Metaphorical use of 'pol' (bridge) in a technical context.

2

پیچیدگی الگوریتم‌های داده‌کاوی نیازمند قدرت محاسباتی بالایی است.

The complexity of data mining algorithms requires high computational power.

Complex noun phrase as subject.

3

داده‌کاوی در علوم اجتماعی برای تحلیل شبکه‌های پیچیده انسانی به کار گرفته می‌شود.

Data mining is utilized in social sciences to analyze complex human networks.

Formal passive 'be kār gerefte šodan'.

4

استفاده غیراخلاقی از داده‌کاوی می‌تواند منجر به نقض گسترده حقوق شهروندی گردد.

Unethical use of data mining can lead to widespread violation of civil rights.

Formal verb 'gaštan' instead of 'šodan'.

5

داده‌کاوی متن یا همان متن‌کاوی، حوزه‌ای است که با داده‌های متنی ساختارنیافته سروکار دارد.

Text data mining, or text mining, is a field that deals with unstructured textual data.

Relative clause with 'ke' and 'sar-o-kār dāštan' (to deal with).

6

ارزیابی دقت مدل‌های داده‌کاوی از اهمیت ویژه‌ای در پژوهش‌های علمی برخوردار است.

Evaluating the accuracy of data mining models is of particular importance in scientific research.

Formal expression 'az ahamiyat-e viže-yi barxordār budan'.

7

داده‌کاوی اکتشافی به دنبال یافتن فرضیات جدید در مجموعه‌داده‌های ناشناخته است.

Exploratory data mining seeks to find new hypotheses in unknown datasets.

Use of 'be donbāl-e' (seeking).

8

تلفیق داده‌کاوی با اینترنت اشیاء، چشم‌اندازهای جدیدی در صنعت ایجاد کرده است.

The integration of data mining with the Internet of Things has created new horizons in the industry.

Compound subject and present perfect verb.

1

پارادایم‌های حاکم بر داده‌کاوی معاصر، به شدت تحت تأثیر پیشرفت‌های یادگیری عمیق قرار گرفته‌اند.

The prevailing paradigms in contemporary data mining have been heavily influenced by advances in deep learning.

Highly academic terminology.

2

داده‌کاوی در تراز کلان، ابزاری است برای حکمرانی داده‌محور و بهینه‌سازی ساختارهای اقتصادی.

Data mining at a macro level is a tool for data-driven governance and optimization of economic structures.

Compound adjectives like 'dāde-mehvar' (data-driven).

3

چالش‌های معرفت‌شناختی داده‌کاوی، پرسش‌هایی را در مورد ماهیت علیت در برابر همبستگی برمی‌انگیزد.

The epistemological challenges of data mining provoke questions about the nature of causality versus correlation.

Formal verb 'bar-angix-tan' (to provoke/arouse).

4

داده‌کاوی جریانی، نیازمند الگوریتم‌هایی است که قادر به پردازش بلادرنگ داده‌های حجیم باشند.

Stream data mining requires algorithms capable of real-time processing of voluminous data.

Technical term 'belā-darang' (real-time).

5

تحلیل‌های پیش‌بینانه در داده‌کاوی، افق‌های نوینی را در مدیریت ریسک‌های مالی گشوده‌اند.

Predictive analytics in data mining have opened new horizons in financial risk management.

Metaphorical formal language.

6

بومی‌سازی ابزارهای داده‌کاوی برای زبان فارسی، مستلزم درک عمیق از ویژگی‌های صرفی و نحوی این زبان است.

Localizing data mining tools for the Persian language requires a deep understanding of the morphological and syntactic features of this language.

Technical linguistic terminology.

7

داده‌کاوی توزیع‌شده، راهکاری کارآمد برای مقابله با محدودیت‌های حافظه در سیستم‌های متمرکز است.

Distributed data mining is an efficient solution for addressing memory limitations in centralized systems.

Adjective 'kār-āmad' (efficient).

8

ضرورت تبیین‌پذیری در داده‌کاوی، منجر به ظهور حوزه‌ای تحت عنوان هوش مصنوعی قابل توضیح شده است.

The necessity of explainability in data mining has led to the emergence of a field known as explainable AI.

Abstract noun 'tabyin-paziri' (explainability).

よく使う組み合わせ

تکنیک‌های داده‌کاوی
الگوریتم‌های داده‌کاوی
پروژه داده‌کاوی
ابزارهای داده‌کاوی
متخصص داده‌کاوی
داده‌کاوی آموزشی
داده‌کاوی در پزشکی
داده‌کاوی پیش‌بینانه
فرآیند داده‌کاوی
نتایج داده‌کاوی

よく使うフレーズ

انجام داده‌کاوی

— To perform data mining. This is the most common verb pairing.

ما باید روی این فایل‌ها داده‌کاوی انجام دهیم.

حوزه داده‌کاوی

— The field of data mining. Used to describe a professional or academic area.

او سال‌ها در حوزه داده‌کاوی فعالیت کرده است.

داده‌کاوی روی داده‌های بزرگ

— Data mining on big data. A very common phrase in modern tech.

داده‌کاوی روی داده‌های بزرگ چالش‌های فنی زیادی دارد.

کاربرد داده‌کاوی

— Application of data mining. Used when discussing how it's used in real life.

کاربرد داده‌کاوی در امنیت سایبری بسیار حیاتی است.

داده‌کاوی متنی

— Textual data mining. Specifically mining text documents.

داده‌کاوی متنی برای تحلیل نظرات کاربران عالی است.

داده‌کاوی وب

— Web mining. Extracting patterns from the internet.

گوگل از داده‌کاوی وب برای رتبه‌بندی سایت‌ها استفاده می‌کند.

داده‌کاوی بصری

— Visual data mining. Using visualization to find patterns.

داده‌کاوی بصری به درک بهتر نمودارها کمک می‌کند.

داده‌کاوی بلادرنگ

— Real-time data mining. Mining data as it is generated.

بورس به داده‌کاوی بلادرنگ نیاز دارد.

مدل داده‌کاوی

— Data mining model. The specific algorithm or structure created.

مدل داده‌کاوی ما دقت ۹۰ درصدی دارد.

دوره آموزشی داده‌کاوی

— Data mining training course.

من در یک دوره آموزشی داده‌کاوی ثبت‌نام کردم.

慣用句と表現

"در داده‌ها غرق شدن"

— To be drowning in data. Used when there is too much information to process without mining.

م

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