Automated Indexation Explained In 4 Easy Steps


Automated Indexation: 4 Easy Steps

When you have gathered big data in the form of unstructured text that you want to categorize, Automated Indexation is the process you need to know about. This process can give data meaning, logic, and information. You can create a search engine where people can find things useful when they search for those. Making sense of it by adding an extra value is the task that you can do with it. Automated Indexation is a core algorithm, which is an essential part of the automated cataloguer.  Hence, it is known as an indexer as well.

Automated Indexation Explained In 4 Easy Steps
Automated Indexation Explained In 4 Easy Steps

Now, we will know about the 4 easy steps of Automated Indexation so that we can evaluate how it works. These steps are shared by the experts, who have a long experience in this subject. When we know about these 4 steps, applying it will be easier as we will know where and when to apply it. So, why wait anymore? Let us know the terms of Automated Indexation and its 4 steps.

The Detail Of Indexation

Firstly, let us assume that your data includes pages or articles, subject lines, and authors. When it comes to the pages or articles, we can assume that it is a web page or the body of an email. By subject lines, we mean page title and by authors, we mean the author of a web page or an email. We already know that these pages are loaded with big text files in folders and subfolders or multiple servers. Also, the timestamps are attached to the documents in some cases. It also may increase the accuracy of the indexer. Even when you only have pages, Automated Indexation is going to work. When you have both pages and authors, it will separate them and then blend the results to maximize accuracy.

Automated Indexation: 4 Easy Steps

Automated Indexation Explained In 4 Easy Steps
Automated Indexation Explained In 4 Easy Steps

Step 1: In this step, you need to create a data dictionary, which is also known as the frequency table. The dictionary will include one-token and two-token keywords found in the pages. The keywords may be from the body or the title of the pages. This one perfectly assumes that you have crawled all the articles to extract the text.

Step 2: The second step is a filter or clean results. Usually, it ignores the keywords that have less than 5 occurrences. Firstly, it checks all the n-grams of a keyword and then, eliminates the ones with a low frequency. This step is initiated when you want to transform unstructured data into meaningful and structured data.

Step 3: The third step manually assigns the seed keywords into multiple categories. The categories are usually pre-selected manually and then the process proceeds. The purpose of this step is to categorize the keywords that are similar or close to each other. Sometimes, there is also a top category named unknown.

Step 4: After the keywords are categorized, it is time to assign the article in question to the top category. This step concludes the entire process of Automated Indexation. Without this step, a complete Automated Indexation won’t be possible, as the experts suggest.

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