Extractive Summarization with BERT Extractive Summarizer

Extractive Summary Tool and BERT Extractive Summarizer

Extractive Text Summarization with BERT Extractive Summarizer involves summarizing an article with the extracted key information via BERT natural language model. Extractive summarization is to provide decreased memory usage while protecting the content’s value. Information about the content is protected via extractive summarizers. BERT is used to understand human languages via RNN, Attention mechanisms, and … Read more

NLTK and Python WordNet: Find Synonyms and Antonyms with Python

NLTK Wordnet for Synonym Finding

NLTK Wordnet can be used to find synonyms and antonyms of words. NLTK Corpus package is used to read the corpus to understand the lexical semantics of the words within the document. A WordNet involves semantic relations of words and their meanings within a lexical database. The semantic relations within the WordNet are hypernyms, synonyms, … Read more

NLTK Lemmatization: How to Lemmatize Words with NLTK?

NLTK Lemmatization

NLTK Lemmatization is the process of grouping the inflected forms of a word in order to analyze them as a single word in linguistics. NLTK has different lemmatization algorithms and functions for using different lemma determinations. Lemmatization is more useful to see a word’s context within a document when compared to stemming. Unlike stemming, lemmatization … Read more

NLTK Stemming Words: How to Stem with NLTK?

NLTK Stemming

NLTK Stemming is a process to produce morphological variations of a word’s original root form with NLTK. Stemming is a part of linguistic morphology and information retrieval. The root of the stemmed word has to be equal to the morphological root of the word. Stemming algorithms and stemming technologies are called stemmers. Natural Language Tool … Read more

NLTK Tokenize: How to Tokenize Words and Sentences with NLTK?

NLTK Tokenization

To tokenize sentences and words with NLTK, “nltk.word_tokenize()” function will be used. NLTK Tokenization is used for parsing a large amount of textual data into parts to perform an analysis of the character of the text. NLTK for tokenization can be used for training machine learning models, Natural Language Processing text cleaning. The tokenized words … Read more

How to Use Bertopic for Topic Modeling and Content Analysis?

topic modeling berttopic

BERTopic is a topic clustering and modeling technique that uses Latent Dirichlet Allocation. Bertopic can be used to visualize topical clusters and topical distances for news articles, tweets, or blog posts. Bertopic can be installed with the “pip install bertopic” code line, and it can be used with spacy, genism, flair, and use libraries for … Read more

How to Translate a Website within Pandas Dataframe via Python?

Translate a Website with Python

Translating a data frame is the process of changing a data frame values’ language to another language without changing the context, meaning, or content. Translating a Pandas Data Frame with Python can be done with Google’s “googletrans” library. In this article, I will crawl a website by taking its semantic content into a data frame … Read more

Download Images from Website with Python in Scale

Download Images with Python

Downloading all images from a website can be done by downloading all of the websites, or crawling all of the websites and extracting all of the “<img>” HTML Elements’ “src” attributes’ values. Usually, scraping and downloading images from websites is important and necessary for image optimization, compression, or writing alt tags with AI or the … Read more

Data Science SEO and Visualization: Retrieving SERP, Crawling Landing Pages, and Analyzing Google Algorithms with Python

SEO Data Science

This article has been prepared as a tutorial to show how to Retrieve Google SERP with regular periods, animate the differences to see Google Search Engine’s preference and experiment algorithms. In this article, we will use Semantic Search Queries to understand the topical coverage and topical authority of certain domains. We will retrieve all of … Read more

How to use Google Knowledge Graph API via Python and Advertools?

Entity SEO Knowledge Graph

Google Knowledge Graph produces Knowledge Panels for entities that are reliable and have enough “Search Demand”. Knowledge Panels that appear in SERP show the relationships of related entities and how Google interprets the character of queries and search intent. More information is available on Knowledge Graph and Knowledge Panel features that are of great value … Read more

How to Create an Entity Relation Diagram with Information Extraction with Python for SEO?

Knowledge Graph Creation via Python for SEO

A knowledge graph is a graph that consists of different types of entities and their connection to each other. Search Engines create a Knowledge Graph while crawling the web so that they can easily detect the relations between entities and understand the purpose of the web page or relevance of the web page for certain … Read more

How to Perform a Content Analysis based on Sitemaps via Python

Content Analysis via Python and Sitemaps

A sitemap is the name of an XML File that collects URLs that must be indexed by the Search Engine on a website. Sitemap Files can contain data on URL Categories, URL publishes date, URL content, content-language, content author, subject, etc. An experienced Holistic SEO can analyze a website even manually through Sitemaps. In this … Read more

How to Categorize URL Parameters and Queries via Python for Analyzing SEO

How to Categorize URLs via Python

URL Parameters are important for SEO and Search Engine Crawlers. Different parameters can have different functions and meanings for both users and Search Engines. Complex URL Parameters can confuse the Search Engine’s Algorithms and create Ranking Signal Dilution in terms of SEO. Also, using and creating unnecessary repetitive and duplicate content with looping products, services … Read more

How to Check Grammar and Language Errors in Content via Python?

Check Grammar Errors with Python

When it comes to SEO, spelling errors, word errors, inverted sentences are factors that affect the user experience and damage the publisher’s expertise. Google Algorithm has been competing since the era of Panda and RankBrain Algorithms to spot both “stemming” and spelling errors, correct them, and rewrite queries. Google has also released a style guideline … Read more

How to Perform Text Analysis via Python and Advertools

Text Analysis with Python

Text or content is a written source that conveys certain information in a certain structure, emotion and voice, and with different methodologies. Each piece of writing can be perceived as better with a specific subject in different aspects. Using different spelling techniques, sentence structures, or using different words makes the two texts on the same … Read more

PyTrend Guideline: Create Dashboard for Google Trends with Python

Pytrend SEO Usage

Google Trend is an application of Google which shows the search terms’ trends over time for different geographies. It shows real-time search trends and daily search trends for every city in the world. Thanks to Google Trend, understanding the users’ intent through different seasons for different queries is easier. Also, real-time events and real-world entities … Read more

How to Resize Images with Python in Bulk

Resize Images in Bulk with Python

Image manipulation, optimization and resizing or downscaling, color type changing, or other kinds of image-related processes have value for SEO, UX, Page Speed, and Bandwith. Because of those motivations, Image Compression Algorithms are developed every year. In this article, we will focus on how to resize multiple images in bulk with Python. For multiple images … Read more