One thing that comes to your mind when you read the word search is ‘keywords’. Search engines have been dependent on keywords for a long time now. Much like before reading a text, you go through the content to find out if any word matches your requirement. Search engines have always been designed in a way to match the exact queries of the users.
Now, it is a struggle to put every keyword in the content. So, after a lot of research, recently, the search feature has been experiencing a shift from that traditional concept of matching. Unlike before, now it is more about apprehension. With the help of artificial intelligence, the way ‘search’ functions is changing, and it is getting more conceptual than being dependent on keywords.
Concept-based search is new in this market. It is used to find out information and data without phrasing the query with the use of proper keywords. Now you must be wondering how is it possible to search for something without a keyword? Let’s look into the concept of concept search to know better.
What is Concept Search?
To understand this search type, firstly let’s look into traditional keyword-based search models, and how it works. In business, the majority of the data is not structured, and to search for items from properly structured data, search engines are the essential tool. The way it is mainly done is through the formation of keywords that are linked to the main data.
However, there are some limitations to this method. For example, keywords can be limiting the search because of various reasons like the existence of synonyms, sequential order, homonyms, and asymmetrical keywords may often not allow users to get their desired results for the queries.
How Does Conceptual Search Work?
Keywords act as a binary when it comes to search, as either it matches the query or it doesn’t. Conceptual Search, however, is dependent on measuring the closeness of the search query to the result. It primarily uses vector algorithms to measure the similarities as well as differences.
Unlike normal search methods, where matching keywords is a necessity, this new search feature widens the possibility as it understands the concept behind the search.
Let’s look into this example to know it better. Technically, ‘outfit’ and ‘cloth’ are two separate terms. But they mean similar things. According to that, if a user searches the word “outfit”, normally the results should only show the ones with the keyword “outfit”. But the concept-based search will show search results that contain data where the word cloth is also present. Because they mean the same thing.
How to Use It?
This search feature allows users to enter a whole document or a sentence that contains the query concept. A single word is not recommended, as it can show a wide range of results that might be unnecessary. The match is not built on one particular term that is in the query. The document and the search query may, or may not share terminologies but they share meaning based on concept.
This does not only apply to documents or only written materials. All information that can be searched has a vector in the conceptual space, and so does each term in the concept index. When these vectors are close enough, they share an intricate conceptual relationship. If these vectors aren’t close, there will be no or less conceptual correlation. By this concept, related images will also pop up while you’re searching for similar things.
Benefits of Concept Searching
Now, let’s talk about how this search will benefit you.
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Removes the Keyword Issue
There are many complexities when it comes to language so keywords may not be enough when it comes to search queries. These problems mainly revolve around the lack of a match between the terminologies. It can be one word having more than one meaning, or multiple words sharing the same meaning.
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More Accurate Result
It gives a more accurate result, as it finds a way around these problems because this search is not dependent on keyword matching to find out relevant information.
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Uses a Holistic Approach
Concept-based search sees documents through a holistic approach, and therefore it can be successful in searching for conceptual meaning in documents. You might even miss the keyword, but this feature will catch it either way.
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Relevant Conceptual Results
This search has its focus on conceptual relevance and is not bothered to match on a single-term basis.
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Allows Descriptive Queries
As it allows users to enter long queries, users are free to express their requirements through the description of ideas. Concept search primarily functions by searching correlations.
This search is very effective however it is dependent on various elements from the information available on the data that is being searched, the engine that is used to search the query, and so on. It has proven to be most effective for specific types of queries like full sentences, and bigger paragraphs that can fully comprehend the query instead of a query composed of a few words, as they are less likely to help you get relevant information.
Switch to Non-Restrictive Search
Using concept-based search in business can be extremely beneficial as it allows for correlating the searches, and also understands the customers’ query concepts, and gives out results accordingly. Keyword-based search can be restrictive but the concept-based approach is more flexible and provides a wide range of results that can be accurate to what customers are looking for. Using this search type will help to develop the search function of your E-commerce website to a considerable extent that your competitors can’t achieve.
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