To search for something online, we have been using the traditional keyword-based search for years. However, this method has its limitations, especially when it comes to finding accurate results for long-tailed queries. Vector search is a new technique that solves this problem by using complex algorithms to match the vectors of the query with those of the database.
In this post, we will discuss what vector search is and how it works. We will also include a PHP client code for vector search, embedded in HTML tags. Finally, we will discuss how WPSOLR can help with vector search.
What is vector search?
Vector search is a technique used to find search results based on the vector space model. In the vector space model, each document is represented as a vector in a high-dimensional space. The dimensions represent the terms in the document, and the entries in the vector represent the frequency of each term in the document.
For example, consider the following two documents:
1. The cat in the hat.
2. The dog in the hat.
The vector representation of these documents can be:
1. (the: 1, cat: 1, in: 1, hat: 1, dog: 0)
2. (the: 1, cat: 0, in: 1, hat: 1, dog: 1)
In the vector space model, each document becomes a point in a high-dimensional space. The similarity between two documents can be measured by the cosine of the angle between the two vectors.
Vector search takes this model one step further. It represents each query as a vector in the same high-dimensional space. The algorithm then finds the documents whose vectors are closest to the query vector.
How does vector search work?
Vector search works by using complex algorithms to match the vectors of the query with those of the database. There are two main components of vector search: indexing and querying.
Indexing: The first step in vector search is to index the data. This involves converting each document into its vector representation, as discussed earlier. The vectors are then stored in a database, along with their corresponding document IDs.
Querying: When a user submits a query, the search engine converts the query into a vector representation. The query vector is then compared with the vectors in the database, and the documents with the closest vectors are returned as search results.
PHP client for vector search
Here is an example PHP client code for vector search:
// Connect to the database $db = new PDO('mysql:host=localhost;dbname=mydb', 'myuser', 'mypassword'); // Prepare the query $query = "SELECT * FROM documents WHERE MATCH (vector) AGAINST (:query)"; // Bind the query vector $vector = [1, 0, 1, 1, 0]; // Query vector for "the cat in the hat" $stmt = $db->prepare($query); $stmt->bindParam(':query', $vector); // Execute the query $stmt->execute(); // Fetch the results $results = $stmt->fetchAll(PDO::FETCH_ASSOC);
How WPSOLR can help
WPSOLR is a powerful search plugin for WordPress that supports vector search. It allows you to index your content with vector representations and provides advanced search capabilities, including faceted search and result ranking.
WPSOLR can also help you enhance your search results by integrating with external search engines, such as Solr and Elasticsearch. These search engines are designed to handle large amounts of data and can provide lightning-fast search results.
In conclusion, vector search is a new technique that can provide accurate results for long-tailed queries. It works by using complex algorithms to match the vectors of the query with those of the database. With the help of WPSOLR, you can implement vector search on your WordPress site and provide an improved search experience for your users.