该服务使应用程序经过社交媒体,企业数据或是其余的数据信息得到个性化的看法。该服务利用语言学的分析方法,经过来自诸如邮件、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。html
经过对复杂社交媒体信息的潜在分析,该服务能够描述出一幅大体的反映用户性格特征的用户画像。基于这些结果,这个服务还能够推断出消费习惯,经过带有时间戳的JSON数据,能够得到消费的时间行为。json
关于本服务描述的性格特征模型详见个性化模型segmentfault
关于消费模型,详见消费偏好api
在bluemix上建立该服务实例,而且得到用户名和密码,具体参见详见Watson使用指南。数组
得到帐户信息(Get profile)app
为输入文本的做者生成一个个性化的帐户。本服务能够得到的最大内容是20MB,能够分析阿拉伯语,英语,日语,或是西班牙语。ide
参数:ui
text (string型,最大20MB)code
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)htm
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,惟一标识代表结果类型)
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,惟一标识代表结果类型)
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,类别惟一标识)
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,惟一标识)
name(string型,偏好名称)
score (number型,偏好得分:0.0(不喜欢)、0.5(通常)、1.0(喜欢))
warnings (对象,必须,警告信息)
warning_id (string型,必须,惟一标识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...
该服务使用语言学的分析方式检测情感语调,社交倾向和书面写做风格
在bluemix上建立该服务实例,而且得到用户名和密码,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')
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 (所有文档的语调分析)
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 (语调惟一标识)
category_id (语调类别)
category_name (类别名)
sentences_tone (句子层次语调分析)
sentence_id (句子惟一编号)
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" } ] } }