bm25相关定义自行查阅,本章着重介绍 Idf 和 tfNorm
idf(term)
idf(term), computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5))
docCount：查询文档集数目，是所在shard的文档数,而不是以索引为单位,这也就能解释为何同一个term对应的Idf是变化的
docFreq：该 term 所命中的文档数目
tfNorm
tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:
示例
- 写入文档
"title": "51信用卡(02051): ５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接 - 雪球",
"content": "５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接"
"title": "51信用卡管家里的投资靠谱吗？",
"content": "谁用过，试了下还信用卡的券还是挺好用的，投资不晓得靠谱吗"
"title": "51信用卡“费马”营销解决方案获得营销服务奖项",
"content": "5月30日，“2019Topdigital创新盛典”在上海龙之梦大酒店顺利举行，会议邀请了众多业内企业领袖、行业专家等来到现场，围绕“新智能”、“新消费”、“新营销”三大主题展开讨论。 作为金融科技头部上市平台，51信用卡也受邀出席本次会议。同时，51信用卡旗下“费马”全生命周期营销解决方案一举摘得当天产品与服务—营销服务奖项。 随着大数据、云计算、人工智能等技术的快速发展和普及，当今世界已经进入到一个快速发展的数字化时代，银行业进入转型升级周期，但在营销获客层面仍面临较多难题。因此，银行业亟需利用大数据技术进行获客、用户运营、经营模式的改造，以实现降本增效的目标。 据介绍，由51信用卡自主研发的“费马”全生命周期营销解决方案可以凭借技术的力量，准确预测用户的全生命周期的需求，实现用户金融需求的深度挖掘，并提供从原点到全生命周期的全链路营销方案。 在第一阶段，“费马”主要围绕渠道投放进行用户的首次转化。依托大数据技术展开渠道价值量化和精准实时调控，并通过渠道追踪、意图识别、实时计算等步骤，帮助完成用户的首次转化; 在用户完成注册激活过程中，采用自研渠道追踪、意图识别引擎对用户进行首次转化优化，在注册激活后，仰仗短文本挖掘、用户行为挖掘等51信用卡独有的人工智能技术，充分挖掘用户特征，描绘用户画像，进而实现智能触达和精准营销，完成用户全生命周期价值的挖掘。 据悉，该方案已实际作用于51信用卡的合作银行，并帮助合作银行发卡量由此前3年累计的10万张提高到了单年28万张，大约实现年发卡量8倍以上的增长。 未来，针对不同银行的获客体系和获客规律进行定制化的产品设计与配套服务，费马也将以点、线、面的方式提供多元化可供选择的产品模式，进一步扩大该产品的市场覆盖率。同时，随着5G时代的逐步到来，提前储备和加强大数据技术的应用和处理速度。"
- index settings
{
"similarity":{
"my_bm25":{
"type":"BM25",
"b":"0"
}
}
}
- single field query
query:
{
"match_phrase":{
"content":{
"query":"51信用卡",
"slop":0,
"boost":1
}
}
}
response:
{
"took":10,
"timed_out":false,
"_shards":{
"total":1,
"successful":1,
"skipped":0,
"failed":0
},
"hits":{
"total":2,
"max_score":1.5446091,
"hits":[
{
"_shard":"[mf_index_tf_idf][0]",
"_node":"K2hhx2UGTdWw6mXlYZtNjQ",
"_index":"mf_index_tf_idf",
"_type":"docs",
"_id":"3",
"_score":1.5446091,
"_source":{
"title":"51信用卡“费马”营销解决方案获得营销服务奖项",
"content":"5月30日，“2019Topdigital创新盛典”在上海龙之梦大酒店顺利举行，会议邀请了众多业内企业领袖、行业专家等来到现场，围绕“新智能”、“新消费”、“新营销”三大主题展开讨论。 作为金融科技头部上市平台，51信用卡也受邀出席本次会议。同时，51信用卡旗下“费马”全生命周期营销解决方案一举摘得当天产品与服务—营销服务奖项。 随着大数据、云计算、人工智能等技术的快速发展和普及，当今世界已经进入到一个快速发展的数字化时代，银行业进入转型升级周期，但在营销获客层面仍面临较多难题。因此，银行业亟需利用大数据技术进行获客、用户运营、经营模式的改造，以实现降本增效的目标。 据介绍，由51信用卡自主研发的“费马”全生命周期营销解决方案可以凭借技术的力量，准确预测用户的全生命周期的需求，实现用户金融需求的深度挖掘，并提供从原点到全生命周期的全链路营销方案。 在第一阶段，“费马”主要围绕渠道投放进行用户的首次转化。依托大数据技术展开渠道价值量化和精准实时调控，并通过渠道追踪、意图识别、实时计算等步骤，帮助完成用户的首次转化; 在用户完成注册激活过程中，采用自研渠道追踪、意图识别引擎对用户进行首次转化优化，在注册激活后，仰仗短文本挖掘、用户行为挖掘等51信用卡独有的人工智能技术，充分挖掘用户特征，描绘用户画像，进而实现智能触达和精准营销，完成用户全生命周期价值的挖掘。 据悉，该方案已实际作用于51信用卡的合作银行，并帮助合作银行发卡量由此前3年累计的10万张提高到了单年28万张，大约实现年发卡量8倍以上的增长。 未来，针对不同银行的获客体系和获客规律进行定制化的产品设计与配套服务，费马也将以点、线、面的方式提供多元化可供选择的产品模式，进一步扩大该产品的市场覆盖率。同时，随着5G时代的逐步到来，提前储备和加强大数据技术的应用和处理速度。"
},
"_explanation":{
"value":1.5446092,
"description":"sum of:",
"details":[
{
"value":1.5446092,
"description":"weight(content:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":1.5446092,
"description":"score(doc=0,freq=5.0 = phraseFreq=5.0 ), product of:",
"details":[
{
"value":0.87059784,
"description":"idf(), sum of:",
"details":[
{
"value":0.47000363,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":2,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1.7741936,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":5,
"description":"phraseFreq=5.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":270,
"description":"avgFieldLength",
"details":[
]
},
{
"value":728,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
},
{
"value":0,
"description":"match on required clause, product of:",
"details":[
{
"value":0,
"description":"# clause",
"details":[
]
},
{
"value":1,
"description":"DocValuesFieldExistsQuery [field=_primary_term]",
"details":[
]
}
]
}
]
}
},
{
"_shard":"[mf_index_tf_idf][0]",
"_node":"K2hhx2UGTdWw6mXlYZtNjQ",
"_index":"mf_index_tf_idf",
"_type":"docs",
"_id":"1",
"_score":0.87059784,
"_source":{
"title":"51信用卡(02051): ５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接 - 雪球",
"content":"５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接"
},
"_explanation":{
"value":0.87059784,
"description":"sum of:",
"details":[
{
"value":0.87059784,
"description":"weight(content:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":0.87059784,
"description":"score(doc=0,freq=1.0 = phraseFreq=1.0 ), product of:",
"details":[
{
"value":0.87059784,
"description":"idf(), sum of:",
"details":[
{
"value":0.47000363,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":2,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":1,
"description":"phraseFreq=1.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":270,
"description":"avgFieldLength",
"details":[
]
},
{
"value":39,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
},
{
"value":0,
"description":"match on required clause, product of:",
"details":[
{
"value":0,
"description":"# clause",
"details":[
]
},
{
"value":1,
"description":"DocValuesFieldExistsQuery [field=_primary_term]",
"details":[
]
}
]
}
]
}
}
]
}
}
- 解释
可以看到 docCount: 3, docFreq: 2(在content field中,有两篇是命中的); 两篇命中文档的IDF score 是一致的
- mutilate fields query
query:
[
{
"match_phrase": {
"content": {
"query": "51信用卡",
"slop": 0,
"boost": 1
}
}
},
{
"match_phrase": {
"title": {
"query": "51信用卡",
"slop": 0,
"boost": 1
}
}
}
]
reponse:
{
"took":15,
"timed_out":false,
"_shards":{
"total":1,
"successful":1,
"skipped":0,
"failed":0
},
"hits":{
"total":3,
"max_score":2.0787346,
"hits":[
{
"_shard":"[mf_index_tf_idf][0]",
"_node":"K2hhx2UGTdWw6mXlYZtNjQ",
"_index":"mf_index_tf_idf",
"_type":"docs",
"_id":"3",
"_score":2.0787346,
"_source":{
"title":"51信用卡“费马”营销解决方案获得营销服务奖项",
"content":"5月30日，“2019Topdigital创新盛典”在上海龙之梦大酒店顺利举行，会议邀请了众多业内企业领袖、行业专家等来到现场，围绕“新智能”、“新消费”、“新营销”三大主题展开讨论。 作为金融科技头部上市平台，51信用卡也受邀出席本次会议。同时，51信用卡旗下“费马”全生命周期营销解决方案一举摘得当天产品与服务—营销服务奖项。 随着大数据、云计算、人工智能等技术的快速发展和普及，当今世界已经进入到一个快速发展的数字化时代，银行业进入转型升级周期，但在营销获客层面仍面临较多难题。因此，银行业亟需利用大数据技术进行获客、用户运营、经营模式的改造，以实现降本增效的目标。 据介绍，由51信用卡自主研发的“费马”全生命周期营销解决方案可以凭借技术的力量，准确预测用户的全生命周期的需求，实现用户金融需求的深度挖掘，并提供从原点到全生命周期的全链路营销方案。 在第一阶段，“费马”主要围绕渠道投放进行用户的首次转化。依托大数据技术展开渠道价值量化和精准实时调控，并通过渠道追踪、意图识别、实时计算等步骤，帮助完成用户的首次转化; 在用户完成注册激活过程中，采用自研渠道追踪、意图识别引擎对用户进行首次转化优化，在注册激活后，仰仗短文本挖掘、用户行为挖掘等51信用卡独有的人工智能技术，充分挖掘用户特征，描绘用户画像，进而实现智能触达和精准营销，完成用户全生命周期价值的挖掘。 据悉，该方案已实际作用于51信用卡的合作银行，并帮助合作银行发卡量由此前3年累计的10万张提高到了单年28万张，大约实现年发卡量8倍以上的增长。 未来，针对不同银行的获客体系和获客规律进行定制化的产品设计与配套服务，费马也将以点、线、面的方式提供多元化可供选择的产品模式，进一步扩大该产品的市场覆盖率。同时，随着5G时代的逐步到来，提前储备和加强大数据技术的应用和处理速度。"
},
"_explanation":{
"value":2.0787349,
"description":"sum of:",
"details":[
{
"value":2.0787349,
"description":"sum of:",
"details":[
{
"value":1.5446092,
"description":"weight(content:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":1.5446092,
"description":"score(doc=0,freq=5.0 = phraseFreq=5.0 ), product of:",
"details":[
{
"value":0.87059784,
"description":"idf(), sum of:",
"details":[
{
"value":0.47000363,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":2,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1.7741936,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":5,
"description":"phraseFreq=5.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":270,
"description":"avgFieldLength",
"details":[
]
},
{
"value":728,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
},
{
"value":0.53412557,
"description":"weight(title:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":0.53412557,
"description":"score(doc=0,freq=1.0 = phraseFreq=1.0 ), product of:",
"details":[
{
"value":0.53412557,
"description":"idf(), sum of:",
"details":[
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":1,
"description":"phraseFreq=1.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":28.666666,
"description":"avgFieldLength",
"details":[
]
},
{
"value":22,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
}
]
},
{
"value":0,
"description":"match on required clause, product of:",
"details":[
{
"value":0,
"description":"# clause",
"details":[
]
},
{
"value":1,
"description":"DocValuesFieldExistsQuery [field=_primary_term]",
"details":[
]
}
]
}
]
}
},
{
"_shard":"[mf_index_tf_idf][0]",
"_node":"K2hhx2UGTdWw6mXlYZtNjQ",
"_index":"mf_index_tf_idf",
"_type":"docs",
"_id":"1",
"_score":1.6050205,
"_source":{
"title":"51信用卡(02051): ５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接 - 雪球",
"content":"５１信用卡 月报表截至2019年5月31日止之股份发行人的证券变动月报表(539KB, PDF) 网页链接"
},
"_explanation":{
"value":1.6050205,
"description":"sum of:",
"details":[
{
"value":1.6050205,
"description":"sum of:",
"details":[
{
"value":0.87059784,
"description":"weight(content:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":0.87059784,
"description":"score(doc=0,freq=1.0 = phraseFreq=1.0 ), product of:",
"details":[
{
"value":0.87059784,
"description":"idf(), sum of:",
"details":[
{
"value":0.47000363,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":2,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":1,
"description":"phraseFreq=1.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":270,
"description":"avgFieldLength",
"details":[
]
},
{
"value":39,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
},
{
"value":0.7344227,
"description":"weight(title:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":0.7344227,
"description":"score(doc=0,freq=2.0 = phraseFreq=2.0 ), product of:",
"details":[
{
"value":0.53412557,
"description":"idf(), sum of:",
"details":[
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1.375,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":2,
"description":"phraseFreq=2.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":28.666666,
"description":"avgFieldLength",
"details":[
]
},
{
"value":50,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
}
]
},
{
"value":0,
"description":"match on required clause, product of:",
"details":[
{
"value":0,
"description":"# clause",
"details":[
]
},
{
"value":1,
"description":"DocValuesFieldExistsQuery [field=_primary_term]",
"details":[
]
}
]
}
]
}
},
{
"_shard":"[mf_index_tf_idf][0]",
"_node":"K2hhx2UGTdWw6mXlYZtNjQ",
"_index":"mf_index_tf_idf",
"_type":"docs",
"_id":"2",
"_score":0.53412557,
"_source":{
"title":"51信用卡管家里的投资靠谱吗？",
"content":"谁用过，试了下还信用卡的券还是挺好用的，投资不晓得靠谱吗"
},
"_explanation":{
"value":0.53412557,
"description":"sum of:",
"details":[
{
"value":0.53412557,
"description":"sum of:",
"details":[
{
"value":0.53412557,
"description":"weight(title:"51 信 用 卡" in 0) [PerFieldSimilarity], result of:",
"details":[
{
"value":0.53412557,
"description":"score(doc=0,freq=1.0 = phraseFreq=1.0 ), product of:",
"details":[
{
"value":0.53412557,
"description":"idf(), sum of:",
"details":[
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
},
{
"value":0.13353139,
"description":"idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
"details":[
{
"value":3,
"description":"docFreq",
"details":[
]
},
{
"value":3,
"description":"docCount",
"details":[
]
}
]
}
]
},
{
"value":1,
"description":"tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
"details":[
{
"value":1,
"description":"phraseFreq=1.0",
"details":[
]
},
{
"value":1.2,
"description":"parameter k1",
"details":[
]
},
{
"value":0,
"description":"parameter b",
"details":[
]
},
{
"value":28.666666,
"description":"avgFieldLength",
"details":[
]
},
{
"value":14,
"description":"fieldLength",
"details":[
]
}
]
}
]
}
]
}
]
},
{
"value":0,
"description":"match on required clause, product of:",
"details":[
{
"value":0,
"description":"# clause",
"details":[
]
},
{
"value":1,
"description":"DocValuesFieldExistsQuery [field=_primary_term]",
"details":[
]
}
]
}
]
}
}
]
}
}
- 解释
_score = weight(content:"51 信 用 卡" in 0) [PerFieldSimilarity] + weight(title:"51 信 用 卡" in 0) [PerFieldSimilarity]
分数是两者之和
转载于:https://www.jianshu.com/p/bc0b89066d04