Automatic indexing is the computerized process of scanning large volumes of documents against a controlled vocabulary, taxonomy, thesaurus or ontology and using those controlled terms to quickly and effectively index large electronic document depositories.
These keywords or language are applied by training a system on the rules that determine what words to match. There are additional parts to this such as syntax, usage, proximity, and other algorithms based on the system and what is required for indexing. This is taken into account using Boolean statements to gather and capture the indexing information out of the text.
Natural language systems
As the number of documents exponentially increases with the proliferation of the Internet, automatic indexing will become essential to maintaining the ability to find relevant information in a sea of irrelevant information. Natural language systems are used to train a system based on seven different methods to help with this sea of irrelevant information.
These methods are
- Semantic, and Pragmatic.
Each of these look and different parts of speed and terms to build a domain for the specific information that is being covered for indexing. This is used in the automated process of indexing.
The automated process can encounter problems and these are primarily caused by two factors:
- The complexity of the language; and,
- The lack intuitiveness and the difficulty in extrapolating concepts out of statements on the part of the computing technology.
Primarily linguistic challenges
These are primarily linguistic challenges and specific problems involve semantic and syntactic aspects of language. These problems occur based on defined keywords. With these keywords you are able to determine the accuracy of the system based on Hits, Misses, and Noise. These terms relate to exact matches, keywords that a computerized system missed that a human wouldn’t, and keywords that the computer selected that a human would not have. The Accuracy statistic based on this should be above 85% for Hits out of 100% for human indexing. This puts Misses and Noise combined to be 15% or less. This scale provides a basis for what is considered a good Automatic Indexing System and shows where problems are being encountered.
Automatic Indexing is the process of assigning documents with search terms for search and retrieval purposes. This process in searches is widely used today to lessen the time of the search. It uses a computer to scan a large volume of documents against a dictionary, rather than manual indexing which makes use of manpower due to manual typing.
Who uses Automatic Indexing?
There are plenty of companies that use automatic indexing today. Even online catalogues, periodical database, and internet search engines use automatic indexing. By automatic indexing, searching is faster and more reliable. One good example is searching for something via the internet and getting fast and reliable results.
What are the possible advantages of Automatic Indexing?
There are numerous advantages to using automatic indexing. One very obvious advantage of automatic indexing is it lessens the job of the user (human) to scan and search a document as fast as how a computer can. Other than that, the computer can also categorize each search it has made. Through this innovation, users are no longer obliged to do such tedious work of scanning, searching and categorizing. However, users may still have to check for errors but it is still considered easier compared to manually doing everything.
Advantages of Automatic Indexing
- More sophisticated than manual indexing
- Great for similar material
- Less expensive
- Can extract terms and cluster them as well
- Can help users find information faster and thoroughly.
- It can be applied to a great number of texts without any hassle.
- Faster, more reliable and cost-effective compared to manual indexing.
- Practically it compensates for difference among the terms used in searches and indexing terms.
While there are advantages in automatic indexing, it also has some disadvantages. For instance, one disadvantage of automatic indexing is, it is not flexible. However, the more it is being used, the system learns even more from the entries made by the users. In finding information, both human and automatic indexing can help users. However, compared to automatic indexing, human or manual indexing takes up a lot of time. It is more tedious and expensive. In terms of technique, automatic indexing has more methods compared to human indexing. To top it all, automatic indexing is well suited for the online environment where there are masses of documents stored and companies with massive amounts of data.