定制 halk/item-similarity 二次开发

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halk/item-similarity

Composer 安装命令:

composer require halk/item-similarity

包简介

Content-based, schema-less recommendation service

README 文档

README

Build Status Code Coverage GitHub license

Item Similarity: content-based, schema-less recommendation service

A simple recommendation service which computes the similarity of items.

Since this is part of my ongoing MSc project, README will be improved by October.

Concept

Similarity Computation

The similarity between two items is computed as follows:

Given the following two JSON documents:

a = {
    "brand": "Addi",
    "model": "Speedy",
    "colors": ["black", "white"],
    "category": "Shoes",
    "size": 42
}
b = {
    "brand": "Prima",
    "model": "Kazak",
    "colors": ["red", "white"],
    "category": "Sweater",
    "sleeves": "long"
}

First, any item features which are not in both documents are discared:

a = {
    "brand": "Addi",
    "model": "Speedy",
    "colors": "black,white",
    "category": "Shoes",
}
b = {
    "brand": "Prima",
    "model": "Kazak",
    "colors": "red,white",
    "category": "Sweater",
}

Second, the documents are converted into lists with the keys as a prefix to the values:

a = ["brand_Addi", "model_Ayak", "colors_black", "colors_white", "category_Shoes"]
b = ["brand_Addi", "model_Kazak", "colors_red", "colors_white", "category_Sweater"]

Finally, the variant of the tanimoto coefficient is calculated:

nA = number of features in A
nB = number of features in B
nAB = number of intersecting features
score = nAB / (nA + nB - nAB)

Similarity index

The index is kept in a MongoDB collection with a document for each feature. This document also keeps track of its similarity score against other documents. Every time a new record is processed, the similarity to other documents is computed and stored. This score is then added to the other document as well. Thus when a similarity score is requested for a document, the end result is already pre-computed.

API

The index is managed by POST and DELETE requests. The score is fetched via GET.

The route prefix {index} allows maintaining more than one index within an instance.

POST /{index} Posts a document to the index and calculates the similarity score

DELETE /{index} Deletes a document

GET /{index}?itemIds=1,2,3 Returns similar items for the items in the GET parameter.

Installation

$ git clone https://github.com/halk/item-similarity
$ cd item-similarity
$ cp config/config.php.dist config/config.php

Please see recowise-vagrant for provisioning details.

Tests

$ cp phpunit.xml.dist phpunit.xml
$ phpunit

halk/item-similarity 适用场景与选型建议

halk/item-similarity 是一款 基于 PHP 开发的 Composer 扩展包,目前已累计 0 次下载、GitHub Stars 达 1, 最近一次更新时间为 2015 年 08 月 21 日, 在 PHP 生态内属于活跃度较高的组件。

它主要适用于以下技术方向: 「recommender」 「content-based filtering」 「recommendation engine」 等业务场景。在实际项目中,围绕这些方向常见需要落地的问题包括:接口对接、性能调优、并发安全、与既有框架(Laravel / ThinkPHP / Yii / Webman 等)的兼容适配,以及生产环境的日志埋点与稳定性保障。

我们在过去多个企业项目中使用过 halk/item-similarity 或与其功能相近的方案,如果你在选型或落地过程中遇到问题,例如 版本兼容、二次改造、私有化封装、与内部系统对接、生产 BUG 排查,欢迎联系我们协助评估。

围绕 halk/item-similarity 我们能提供哪些服务?
定制开发 / 二次开发

基于 halk/item-similarity 在你已有业务上做功能扩展、字段裁剪、UI 适配、与内部账号 / 权限 / 日志系统的深度对接。

BUG 修复 & 性能优化

线上偶发问题、内存泄漏、慢查询、并发异常等排查修复;针对高流量场景做缓存、队列、索引层面的调优。

项目外包 & 长期维护

承接完整的项目从需求 → 设计 → 开发 → 上线 → 长期运维;也可按月提供技术保姆服务。

yvsm@zunyunkeji.com QQ:316430983 微信:yvsm316 西安尊云信息科技 · 专注 PHP / Go / 分布式系统研发

统计信息

  • 总下载量: 0
  • 月度下载量: 0
  • 日度下载量: 0
  • 收藏数: 1
  • 点击次数: 22
  • 依赖项目数: 0
  • 推荐数: 0

GitHub 信息

  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2015-08-21