Somehow, every time a new search engine emerges, we hear a new slogan that predicts the future. Hakia hoped to break the rules as the first ontological semantic and natural language processing (NLP) based search engine, but it lost the war when Powerset, its main strong competitor, sold to Microsoft.
不知何故，每当出现一个新的搜索引擎时，我们都会听到一个新的口号，它可以预测未来。 哈基亚(Hakia)希望打破规则，成为第一个基于本体语义和自然语言处理(NLP)的搜索引擎，但是当它的主要竞争对手Powerset出售给Microsoft时，它输掉了这场战争。
What few know is that all search engines have been using NLP in since the 50s, and all computer programs that deal with language use NLP (including your spell-checker), so bragging about being a NLP-based search engine is not something I’d advise new search engines to do.
鲜为人知的是， 自50年代以来 ，所有搜索引擎一直在使用NLP，并且处理语言的所有计算机程序都使用NLP(包括拼写检查器)，因此吹嘘自己要成为基于NLP的搜索引擎并不是我的本意。 d建议新的搜索引擎来做。
Both hakia and Powerset used to call themselves semantic search engines. This has changed, and both make broader and more realistic claims instead. NLP is not synonymous with semantic search – semantic search is just a part of the technology – and we are still very far from having a true semantic search engine, although many are heading in the right direction.
hakia和Powerset都曾经称自己为语义搜索引擎。 这已经改变了，两者都提出了更广泛，更现实的主张。 NLP不是语义搜索的同义词–语义搜索只是该技术的一部分–尽管许多人都朝着正确的方向前进，但我们离真正的语义搜索引擎还很遥远。
This introduction about NLP and semantic search present a new search engine that has a clearly defined point: Jinni, the new video search engine self-labeled as the “first Taste Engine,” states among its algorithms semantic search technology and personal recommendations, both based on Natural Language Processing and taste profiling. We have to understand from the start that such claims, without access to the algorithms, cannot be sustained by any journalist. As far as the search engines making the claims go, any new innovation needs to capitalize on something, and the idea of semantic search is nebulous enough to allow such PR tweaks.
有关NLP和语义搜索的介绍提出了一个具有明确定义点的新搜索引擎： Jinni (自标记为“第一个味觉引擎”的新视频搜索引擎)在其算法中陈述了语义搜索技术和个人推荐，两者均基于关于自然语言处理和味道分析。 我们必须从一开始就理解，这样的主张，如果不能访问算法，就不可能由任何记者来维持。 就提出要求的搜索引擎而言，任何新的创新都需要利用某些东西，而语义搜索的思想还很模糊，无法进行此类PR调整。
More interesting about Jinni, however, is their vision of the future where a search engine becomes personal and results are served based on personalized recommendations. These recommendations are made possible by the core of the engine – the Movie Genome (created by movie professionals) that contains several thousand “genes” assigned to each title to describe plot, mood, style, setting, soundtrack and more – a rich alternative to the usual genre language. From an SEO standpoint, the Movie Genome is a step forward: through tagging page elements and video content, to be more accurately identified and visible for search engines, Jinni actually proposes an improvement to the currently existing algorithms.
但是，对于Jinni而言，更有趣的是他们对未来的愿景，即搜索引擎变得个性化，并根据个性化推荐提供结果。 引擎的核心– 电影基因组 (由电影专业人士创建)使这些建议成为可能，该电影基因组包含数千个“基因”，分配给每个标题以描述情节，心情，风格，背景，配乐等，是替代电影的丰富选择。通常的体裁语言。 从SEO的角度来看，Movie Genome是向前迈出的一步：通过标记页面元素和视频内容，以便更准确地识别搜索引擎并使其可见，Jinni实际上提出了对现有算法的改进。
Another interesting aspect of Jinni is the “pulse” – a feature that shows live streams of users’ actions and opinions. An ongoing monitoring of social networks like Twitter, Facebook and personal blogs is also part of the “pulse” as Jinni wants to be part of the conversation, without actually becoming a social network itself.
Jinni另一个有趣的方面是“脉冲”，该功能可实时显示用户的行为和意见。 由于Jinni希望成为对话的一部分，而实际上并未成为社交网络本身，因此对Twitter，Facebook和个人博客等社交网络进行的持续监视也是“脉冲”的一部分。
An example of "taste profiling" - probably Jinni's most important feature.
“味道分析”的一个示例-可能是Jinni最重要的功能。
Last but not least, the personalized recommendations are indeed personal. There is no “people who like this also like…” as you find on Amazon, Netflix and other similar networks. Jinni’s model is unique. With integration to Netflix, Hulu and other leading content providers, Jinni aims to be the personalized starting point for choosing what to watch next, and according to CNET, “Jinni is the best movie recommendation engine on the Web. Period.” I tend to agree. What’s your opinion?
最后但并非最不重要的一点是，个性化推荐确实是个人的。 在亚马逊，Netflix和其他类似网络上找不到“喜欢它的人也喜欢……”。 珍妮的模型是独一无二的。 通过与Netflix，Hulu和其他领先的内容提供商的集成，Jinni的目标是成为选择下一步观看内容的个性化起点，并且根据CNET的说法， “ Jinni是Web上最好的电影推荐引擎。 期。” 我倾向于同意。 你怎么看？
翻译自: https://www.sitepoint.com/jinni/
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