Information Retrieval Skills and Its Accompanied Benefits For Information Seekers

Information Retrieval Skills and Its Accompanied Benefits For Information Seekers

Information retrieval should become part of schools curriculum as the number of information sought online, and level of information explosion keeps rising. Meaning some people with low technical skills of retrieving information could be having difficulty retrieving information that is acceptable and perfect for their information needs.

So, what is Information retrieval? The definition below is derived from Wikipedia’s definition on Information retrieval.

“Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for metadata that describe data, and for databases of texts, images or sounds.”

An information retrieval process begins when a user enters a query into the system. Queries are formal statements of information needs, for example search strings in web search engines. In information retrieval a query does not uniquely identify a single object in the collection. Instead, several objects may match the query, perhaps with different degrees of relevancy.

An object is an entity that is represented by information in a content collection or database. User queries are matched against the database information. However, as opposed to classical SQL queries of a database, in information retrieval the results returned may or may not match the query, so results are typically ranked. This ranking of results is a key difference of information retrieval searching compared to database searching

The evaluation of an information retrieval system is the process of assessing how well a system meets the information needs of its users. Traditional evaluation metrics, designed for Boolean retrieval or top-k retrieval, include precision and recall. Many more measures for evaluating the performance of information retrieval systems have also been proposed. In general, measurement considers a collection of documents to be searched and a search query. All common measures described here assume a ground truth notion of relevancy: every document is known to be either relevant or non-relevant to a particular query. In practice, queries may be ill-posed and there may be different shades of relevancy.

Virtually all modern evaluation metrics (e.g., mean average precision, discounted cumulative gain) are designed for ranked retrieval without any explicit rank cutoff, taking into account the relative order of the documents retrieved by the search engines and giving more weight to documents returned at higher ranks.

You would agree that information is useless when it is not meeting an information need, making it irrelevant. Hence, knowing how to retrieve information in this day and time is important, if it is to be seen relevant. And reason I join the numbers of experts arguing that information retrieval should be emphasized on.

What do you think as well?