Develop knowledge graph search function using PHP and Manticore Search

Use PHP and Manticore Search to develop knowledge graph search function

Overview:
Knowledge graph is a graph-based knowledge organization and representation method that can Entities, attributes, and relationships are displayed in the form of diagrams. In today's big data era, knowledge graphs are widely used in various fields, such as search engines, intelligent question and answer systems, etc. This article will introduce how to use PHP and Manticore Search to develop a search function based on knowledge graphs, and provide code examples.

1. Install and configure Manticore Search
First, you need to install Manticore Search and configure it. The installation package can be downloaded from the official website (https://manticoresearch.com/downloads/).

After the installation is complete, configuration needs to be performed. Open the manticore.conf file and configure the index path, listening port and other information.

2. Construct knowledge graph data
Before developing the search function, you need to build a knowledge graph data and import the data into Manticore Search. Taking the movie knowledge graph as an example, the data structure is as follows:

1. Entity: movie
   Attributes: movie ID, movie name, director, actor, type, rating, etc.
2. Entity : Actor
   Attributes: Actor ID, actor name, date of birth, gender, etc.
3. Entity: Director
   Attributes: Director ID, director name, date of birth, gender, etc.
4. Relationship : Relationship between actor and movie
   Attributes: Actor ID, movie ID, character name
5. Relationship: Relationship between director and movie
   Attributes: Director ID, movie ID

Import the above data into the Manticore Search index, which can be implemented using Manticore's API. The sample code is as follows:

<?php
// 知识图谱数据导入示例代码
$host = 'localhost';
$port = 9308;

// 连接Manticore Search
$client = new ManticoresearchClient([
    'host' => $host,
    'port' => $port
]);

// 创建索引
$client->indices()->create([
    'index' => 'movies',
]);

// 定义字段
$fields = [
    'id' => ['type' => 'integer'],
    'name' => ['type' => 'text'],
    'director' => ['type' => 'text'],
    'actor' => ['type' => 'text'],
    'genre' => ['type' => 'text'],
    'rating' => ['type' => 'float'],
];

// 创建文档
$movies = [
    ['id' => 1, 'name' => 'The Shawshank Redemption', 'director' => 'Frank Darabont', 'actor' => 'Tim Robbins, Morgan Freeman', 'genre' => 'Drama', 'rating' => 9.3],
    ['id' => 2, 'name' => 'The Godfather', 'director' => 'Francis Ford Coppola', 'actor' => 'Marlon Brando, Al Pacino', 'genre' => 'Crime', 'rating' => 9.2],
    // 其他电影数据...
];

// 将文档添加到索引中
$documents = [];
foreach ($movies as $movie) {
    $document = new ManticoresearchDocument();
    $document->setIndex('movies');
    $document->setId($movie['id']);
    $document->setFields($movie);
    $documents[] = $document;
}

$client->bulk($documents);

// 关闭连接
$client->getConnection()->close();

3. Implementing the knowledge graph search function
The key to knowledge graph search is to construct a suitable query statement , to accommodate different entities and relationships.

The following is a simple movie search example code, which implements the function of searching based on movie name, actor and director:

<?php
// 电影搜索示例代码
$host = 'localhost';
$port = 9308;

// 连接Manticore Search
$client = new ManticoresearchClient([
    'host' => $host,
    'port' => $port
]);

// 构建查询语句
$query = new ManticoresearchQueryBoolQuery();
$query->addMust(new ManticoresearchQueryMatchQuery('name', 'The Shawshank Redemption'));
$query->addMust(new ManticoresearchQueryMatchQuery('actor', 'Morgan Freeman'));
$query->addMust(new ManticoresearchQueryMatchQuery('director', 'Frank Darabont'));

// 执行查询
$search = new ManticoresearchSearch($client);
$search->addIndex('movies');
$search->setQuery($query);
$result = $search->search();

// 输出结果
print_r($result->getDocuments());

// 关闭连接
$client->getConnection()->close();

4. Summary
This article introduces the use of PHP and Manticore Search methods for developing knowledge graph search functions and provides relevant code examples. By properly constructing query statements, accurate and efficient knowledge graph searches can be achieved. At the same time, the powerful functions of Manticore Search make the development of search engines simpler and more convenient. I hope this article can be helpful to you in the development process of knowledge graph search.

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