个性化见解(Personality Insights)
简介
该服务使应用程序通过社交媒体,企业数据或是其他的数据信息获得个性化的见解。该服务利用语言学的分析方法,通过来自诸如邮件、短信、博客和论坛帖子中的数据,推断出一些个体固有的性格特征,包括“Big Five”(注:大五类性格特征分析,一种心理学上的人格划分系统),需求,价值。
通过对复杂社交媒体信息的潜在分析,该服务可以描述出一幅大致的反映用户性格特征的用户画像。基于这些结果,这个服务还可以推断出消费习惯,通过带有时间戳的JSON数据,可以获得消费的时间行为。
关于本服务描述的性格特征模型详见个性化模型
关于消费模型,详见消费偏好
认证
在bluemix上创建该服务实例,并且获得用户名和密码,具体参见详见Watson使用指南。
方法
获得账户信息(Get profile)
为输入文本的作者生成一个个性化的账户。本服务可以获得的最大内容是20MB,可以分析阿拉伯语,英语,日语,或是西班牙语。
参数:
text (string型,最大20MB)
content_type (string型,text/plain(默认)适用纯文本、text/html适用网页、application/json适用JSON数据,使用html或是纯文本时徐添加对数据格式的描述“charset”,例如:content_type=text/plain;charset=utf-8)
content_language (string型, 支持语言ar(阿拉伯语)、en(默认,英语)、es(西班牙语)、ja(日语))
accept (string型,响应类型:application/json、text/csv)
、accept_language(string型,响应语言:ar (阿拉伯)、de (德)、en (英, 默认)、es (西)、fr (法)、it (意)、ja (日)、ko (韩)、pt-br (巴西,葡萄牙)、zh-cn (简体中文)、zh-tw (繁体中文)
raw_scores (bool型, 在标准百分数上是否返回原始得分,设置为false只返回标准百分数)
consumption_preferences (bool型,是否返回消费偏好,设置为false,不返回)
csv_headers (bool型,是否返回一个csv响应)
profile(text, content_type='text/plain', content_language=None,
accept='application/json', accept_language=None, raw_scores=False,
consumption_preferences=False, csv_headers=False)
personality_insights = PersonalityInsightsV3(
version='2016-10-20',
username='{username}',
password='{password}')
with open(join(dirname(__file__), './profile.json')) as profile_json:
profile = personality_insights.profile(
profile_json.read(), content_type='application/json',
raw_scores=True, consumption_preferences=True)
print(json.dumps(profile, indent=2))
返回结果
参数:
word_count (int型,必须,输入文本中的单词数)
processed_language (string型,必须,处理文本语言)
-
personality (对象,必须,大五类人格特征的数组)
trait_id (string型,必须,唯一标识表明结果类型)
name (string型,必须,性格特征)
category (string型,必须,性格类型)
percentile (number型,必须,性格特征得分)
raw_scorce (number型, 原始得分)
children (对象,详细信息)
needs (对象,必须,需求信息的数组,数组详细内容同大五类)
values (对象,必须,价值信息的数组,详细内容同大五类)
-
behavior (对象,有时间信息的详细行为)
trait_id (string型,必须,唯一标识表明结果类型)
name (string型,必须,性格特征)
category (string型,必须,特征类型)
percentage (number型,必须,输入数据的时间百分比)
-
consumption_preferences (对象,消费偏好)
consumption_preference_category_id (string型,必须,类别唯一标识)
name (string型,必须,类别名)
-
consumption_preferences (对象,必须,消费偏好详细信息)
consumption_preference_id (string型,必须,唯一标识)
name(string型,偏好名称)
score (number型,偏好得分:0.0(不喜欢)、0.5(一般)、1.0(喜欢))
-
warnings (对象,必须,警告信息)
warning_id (string型,必须,唯一标识ID)
message (string型,必须,警告信息)
word_count_message (string型)
"word_count": 15223,
"processed_language": "en",
"personality": [
{
"trait_id": "big5_openness",
"name": "Openness",
"category": "personality",
"percentile": 0.8011555009553,
"raw_score": 0.77565404255038,
"children": [
{
"trait_id": "facet_adventurousness",
"name": "Adventurousness",
"category": "personality",
"percentile": 0.89755869047319,
"raw_score": 0.54990704031219
},
. . .
]
},
{
"trait_id": "big5_conscientiousness",
"name": "Conscientiousness",
"category": "personality",
"percentile": 0.81001753184176,
"raw_score": 0.66899984888815,
"children": [
{
"trait_id": "facet_achievement_striving",
"name": "Achievement striving",
"category": "personality",
"percentile": 0.84613299226628,
"raw_score": 0.74240118454888
},
. . .
]
},
{
"trait_id": "big5_extraversion",
"name": "Extraversion",
"category": "personality",
"percentile": 0.64980796071382,
"raw_score": 0.56817738781166,
"children": [
{
"trait_id": "facet_activity_level",
"name": "Activity level",
"category": "personality",
"percentile": 0.88220584913965,
"raw_score": 0.60106995926143
},
. . .
]
},
{
"trait_id": "big5_agreeableness",
"name": "Agreeableness",
"category": "personality",
"percentile": 0.94786124793821,
"raw_score": 0.80677815631809,
"children": [
{
"trait_id": "facet_altruism",
"name": "Altruism",
"category": "personality",
"percentile": 0.99241983824205,
"raw_score": 0.79028406290747
},
. . .
]
},
{
"trait_id": "big5_neuroticism",
"name": "Emotional range",
"category": "personality",
"percentile": 0.5008224041628,
"raw_score": 0.46748200007024,
"children": [
{
"trait_id": "facet_anger",
"name": "Fiery",
"category": "personality",
"percentile": 0.17640022058508,
"raw_score": 0.48490315691802
},
. . .
]
}
],
"needs": [
{
"trait_id": "need_challenge",
"name": "Challenge",
"category": "needs",
"percentile": 0.67362332054511,
"raw_score": 0.75196348037675
},
{
"trait_id": "need_closeness",
"name": "Closeness",
"category": "needs",
"percentile": 0.83802834041813,
"raw_score": 0.83714327329724
},
. . .
],
"values": [
{
"trait_id": "value_conservation",
"name": "Conservation",
"category": "values",
"percentile": 0.89268222856139,
"raw_score": 0.72135308187423
},
{
"trait_id": "value_openness_to_change",
"name": "Openness to change",
"category": "values",
"percentile": 0.85759916388086,
"raw_score": 0.82551308431323
},
. . .
],
"behavior": [
{
"trait_id": "behavior_sunday",
"name": "Sunday",
"category": "behavior",
"percentage": 0.21392532795156
},
{
"trait_id": "behavior_monday",
"name": "Monday",
"category": "behavior",
"percentage": 0.42583249243189
},
. . .
{
"trait_id": "behavior_0000",
"name": "0:00 am",
"category": "behavior",
"percentage": 0.4561049445005
},
{
"trait_id": "behavior_0100",
"name": "1:00 am",
"category": "behavior",
"percentage": 0.12209889001009
},
. . .
],
"consumption_preferences": [
{
"consumption_preference_category_id": "consumption_preferences_shopping",
"name": "Purchasing Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_automobile_ownership_cost",
"name": "Prefers automobile ownership cost",
"score": 0
},
. . .
]
},
{
"consumption_preference_category_id": "consumption_preferences_health_and_activity",
"name": "Health & Activity Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_eat_out",
"name": "Prefers to eat out",
"score": 1
},
. . .
]
},
{
"consumption_preference_category_id": "consumption_preferences_environmental_concern",
"name": "Environmental Concern Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_concerned_environment",
"name": "Likely to be concerned about the environment",
"score": 0
}
]
},
{
"consumption_preference_category_id": "consumption_preferences_entrepreneurship",
"name": "Entreprenuership Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_start_business",
"name": "Likely to start a business in next few years",
"score": 1
}
]
},
{
"consumption_preference_category_id": "consumption_preferences_movie",
"name": "Movie Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_movie_romance",
"name": "Likely to like romance movies",
"score": 1
},
. . .
]
},
{
"consumption_preference_category_id": "consumption_preferences_music",
"name": "Music Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_music_rap",
"name": "Likely to like rap music",
"score": 1
},
. . .
]
},
{
"consumption_preference_category_id": "consumption_preferences_reading",
"name": "Reading Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_read_frequency",
"name": "Reading frequency",
"score": 0
},
. . .
]
},
{
"consumption_preference_category_id": "consumption_preferences_volunteering",
"name": "Volunteering Preferences",
"consumption_preferences": [
{
"consumption_preference_id": "consumption_preferences_volunteer",
"name": "Have volunteering experience",
"score": 0
}
]
}
],
"warnings": []
}
文档原文地址:http://www.ibm.com/watson/dev...
语调分析(Tone Analyzer)
简介
该服务使用语言学的分析方式检测情感语调,社交倾向和书面写作风格
认证
在bluemix上创建该服务实例,并且获得用户名和密码,具体参见详见Watson使用指南。
import json
from watson_developer_cloud import ToneAnalyzerV3
tone_analyzer = ToneAnalyzerV3(
username='YOUR SERVICE USERNAME',
password='YOUR SERVICE PASSWORD',
version='2016-05-19')
方法
语调分析(Analyzer tone)
分析一段文本的语调。语调包括社交态度,感情,语言。每一类都有衍生的更多内容。
参数:
text (query型,GET必须,待分析文档,至少三个单词)
body (body型,POST必须,JSON或纯文本,待分析文档)
Content-Type (header型,POST必须,待分析文档类型)
version (query型, 必须,版本号,当前最新:2016-05-19)
tone (query型,语调分类标签)
sentences (query型,过滤句子层次)
import json
from watson_developer_cloud import ToneAnalyzerV3
tone_analyzer = ToneAnalyzerV3(
username='YOUR SERVICE USERNAME',
password='YOUR SERVICE PASSWORD',
version='2016-05-19 ')
print(json.dumps(tone_analyzer.tone(text='A word is dead when it is said, some say. Emily Dickinson'), indent=2))
返回结果
参数:
document_tone (全部文档的语调分析)
tone_categories(语调类别:感情,语言,社交态度)
tones (具体信息。感情:anger、disgust、fear、joy、sadness;语言:analytical、confident、tentative(试探性);社交态度:openness、conscientiousness(责任)、extraversion(外向)、agreeableness、emotion_range)
score (语调得分)
tone_id (语调唯一标识)
category_id (语调类别)
category_name (类别名)
sentences_tone (句子层次语调分析)
sentence_id (句子唯一编号)
text (正在分析的文本)
input_from (句子中第一个字母的序号)
input_to (句子中最后一个字母的序号)
{
"document_tone": {
"tone_categories": [
{
"tones": [
{
"score": 0.25482,
"tone_id": "anger",
"tone_name": "Anger"
},
{
"score": 0.345816,
"tone_id": "disgust",
"tone_name": "Disgust"
},
{
"score": 0.121116,
"tone_id": "fear",
"tone_name": "Fear"
},
{
"score": 0.078903,
"tone_id": "joy",
"tone_name": "Joy"
},
{
"score": 0.199345,
"tone_id": "sadness",
"tone_name": "Sadness"
}
],
"category_id": "emotion_tone",
"category_name": "Emotion Tone"
},
{
"tones": [
{
"score": 0.999,
"tone_id": "analytical",
"tone_name": "Analytical"
},
{
"score": 0.999,
"tone_id": "confident",
"tone_name": "Confident"
},
{
"score": 0.694,
"tone_id": "tentative",
"tone_name": "Tentative"
}
],
"category_id": "language_tone",
"category_name": "Language Tone"
},
{
"tones": [
{
"score": 0.271,
"tone_id": "openness_big5",
"tone_name": "Openness"
},
{
"score": 0.11,
"tone_id": "conscientiousness_big5",
"tone_name": "Conscientiousness"
},
{
"score": 0.844,
"tone_id": "extraversion_big5",
"tone_name": "Extraversion"
},
{
"score": 0.257,
"tone_id": "agreeableness_big5",
"tone_name": "Agreeableness"
},
{
"score": 0.497,
"tone_id": "emotional_range_big5",
"tone_name": "Emotional Range"
}
],
"category_id": "social_tone",
"category_name": "Social Tone"
}
]
}
}
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