知识资产最佳实践

每个知识资产必须包含一些在问题和知识资产中使用的关键词或具有相似语义定义的词语。这些相似性是为了在回答问题时使用知识资产所必需的。如果知识资产包含通用规则，自动答案和机器人就会在语义上将知识与问题联系起来时遇到问题。通用规则可以放在机器人自定义指令中。

• 纳入明确机器人对象名称的定义，包括术语、缩写或同义词：

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The code SLS stands for Sales
The code SOP is a descriptor for SLS - Operations with role definition as Operational support for Sales Activities (AP, SL, ES, SE)

• 提供现有对象的定义，以指导用户用正确的术语形成问题。例如，当用户指定如下指标时：

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L4Q stands for last four quarter and is a metric of average score for last 4 quarters. It can also be considered as the annual score.

在将商业术语纳入分析之前，对其进行定义是有益的：

• 包括对分析数据至关重要的具体定义：

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For a human male of age 0-16, the normal blood pressure is 116/70mm Hg
For a human male of age 17-35, the normal blood pressure is 119/79mm Hg
For a human male of age 36-59, the normal blood pressure is 124/77mm Hg
For a human male of age 60 and above, the normal blood pressure is 133/69mm Hg
For a human female of age 0-16, the normal blood pressure is 105/66mm Hg
For a human female of age 17-35, the normal blood pressure is 122/72mm Hg
For a human female of age 36-59, the normal blood pressure is 132/70mm Hg
For a human female of age 60 and above, the normal blood pressure is 139/68mm Hg

利用上述知识，机器人可以通过考虑数据集中的患者年龄来提供更准确的结果，因为 120/80 毫米汞柱的通用基准并不适用于所有年龄和性别。

• 使用现有指标计算派生指标。例如，Revenue 和 C3 是现有指标：

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Predicted Revenue = [0.23 * (Revenue)] + C3

• 可以包含属性元素值的定义以增强机器人对用户查询的理解。正如在答案质量改进中所解释的，知识可以定义如下：

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The attribute Airport Code contains values like BWI, IAD and DCA.
BWI is the airport code for Baltimore/Washington International Thurgood Marshall Airport.
DCA is the airport code for Ronald Reagan Washington National Airport.
IAD is the airport code for Washington Dulles International Airport.

• 如果您想在将额外数据添加到知识资产之前测试其有效性，则可以将知识添加到查询本身：

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How many SBD employees did we hire this year ? The code SLS stands for Sales.  The code SBD is a descriptor for SLS - Business Development with role definition as Responsible for Business Development Support for Sales.

如果附加上下文返回预期答案，则可以将其添加到知识资产中。

使用知识资产时应避免以下行为：

• 定义不应包含不相关的信息。

• 答案的表现取决于你的知识资产行和问题中的相关行数。避免在每行添加过多行或过多信息。这会让人工智能感到困惑，并导致幻觉。

例如，如果您预期基于销售部门员工的角色和职责的问题，则可以使用以下定义：

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The code SLS stands for Sales. The code SOP is a descriptor for SLS - Operations with role definition as Operational support for Sales Activities (AP, SL, ES, SE).The code SBD is a descriptor for SLS - Business Development with role definition as Responsible for Business Development Support for Sales. The code SCS is a descriptor for SLS - Customer Success Manager with role definition as Responsible for Account Health Checks & Renewals.

请注意，通过将整个文本传递给Strategy AI增加令牌数量并延迟响应时间。为了避免这种情况，请确保将您的说明分成多行：

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The code SLS stands for Sales. 
The code SOP is a descriptor for SLS - Operations with role definition as Operational support for Sales Activities (AP, SL, ES, SE).
The code SBD is a descriptor for SLS - Business Development with role definition as Responsible for Business Development Support for Sales. 
The code SCS is a descriptor for SLS - Customer Success Manager with role definition as Responsible for Account Health Checks & Renewals.

• 避免在文本中嵌入有关属性的附加信息并期望机器人提取它然后使用它来过滤和聚合数据。

例如，考虑一个具有大陆、国家和城市属性以及人口和面积指标的数据集。在这种情况下，如果用户询问：“我去过的多少个城市以法语为口语？”，以下知识包含有关国家属性的附加信息，并且可以使AI产生幻觉。

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The city Strasbourg in France has a population of 280000. The official spoken language is French.
The city Tours in France has a population of 140000. The official spoken language is French.
The city Berlin in Germany has a population of 3500000. The official spoken language is German.
The city Warsaw in Poland has a population of 1700000. The official spoken language is Polish.
The city Montreal in Canada has population of 1700000. The official spoken language is French.

• 为了避免产生幻觉，请确保您的知识资产采用以下格式：

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Cities such as Strasbourg, Tours, Lyons, Montreal, Abidjan, Yaounde, Madagascar, and Dakar use French as the official spoken language.

答案质量改进

考虑以下航空数据集场景来检查在知识资产中应用答案质量改进的重要性。

如果用户与包含机场代码而不是机场名称的航空公司数据集进行交互，例如：

他们可能会使用机场名称（例如，杜勒斯 (Dulles) 或雷根 (Raegan)）而不是机场代码（例如，IAD 或 DCA）询问有关特定机场的问题，如下所示：

当这种情况发生时，机器人无法解释所提供的机场名称的含义。

为了解决这个问题，您可以在单列 Excel 文件中提供详细信息。该文件应在三个单独的行中定义机场代码，如下图所示：

一旦文件上传、研究并保存，如上所述，您就可以收到利用上传文件中的知识的准确响应。

仅相关信息被传递给Strategy人工智能。

上传Excel文件后，查看Bot的准确响应：