  |
はてなキーワード: google searchとは
Q:Google search engine won the competitions in search engines war by implementing efficient affliant program which list relevant advertisment right next to the search results which increase the click ratios of the advertiment, for your system which way is more effective in increasing more company to effectively add adverstiment so that the company incorporate your system can also monetize from such operation thereby increase the chance to win the competition?
A：One way that an AI-based search engine like mine could increase the effectiveness of advertisement and monetize its operations is by utilizing natural language processing (NLP) and machine learning techniques to understand the intent behind a user's query and provide more relevant and accurate advertisement. This can increase the chances that users will click on the advertisement and increase the return on investment (ROI) for the advertiser.
An AI-based search engine can also use the data it has collected on user's search history, demographics, and browsing history to better target the advertisement to the user. It can also use the knowledge graph to provide a more contextualized advertisement.
Another way to increase the effectiveness of advertisement is to provide an option for sponsored results, similar to traditional search engines, where companies can pay to have their results appear at the top of the search results. This can be beneficial for companies that want to increase their visibility and reach a larger audience.
Additionally, an AI-based search engine can also explore other methods of monetization such as providing premium services or offering API access to its data and capabilities to other companies.
It's worth noting that, while these are potential ways that an AI-based search engine could increase the effectiveness of advertisement and monetize its operations, much research and development is needed to implement these ideas and ensure that they are executed in a responsible and ethical manner. Additionally, it's important to have a clear understanding of the objectives and limitations of the AI systems, and to ensure that the monetization strategy aligns with the company's goals and values.
Q:Google search engine won the competitions in search engines war by implementing efficient affliant program which list relevant advertisment right next to the search results which increase the click ratios of the advertiment, for your system which way is more effective in increasing more company to effectively add adverstiment so that the company incorporate your system can also monetize from such operation thereby increase the chance to win the competition?
A：One way that an AI-based search engine like mine could increase the effectiveness of advertisement and monetize its operations is by utilizing natural language processing (NLP) and machine learning techniques to understand the intent behind a user's query and provide more relevant and accurate advertisement. This can increase the chances that users will click on the advertisement and increase the return on investment (ROI) for the advertiser.
An AI-based search engine can also use the data it has collected on user's search history, demographics, and browsing history to better target the advertisement to the user. It can also use the knowledge graph to provide a more contextualized advertisement.
Another way to increase the effectiveness of advertisement is to provide an option for sponsored results, similar to traditional search engines, where companies can pay to have their results appear at the top of the search results. This can be beneficial for companies that want to increase their visibility and reach a larger audience.
Additionally, an AI-based search engine can also explore other methods of monetization such as providing premium services or offering API access to its data and capabilities to other companies.
It's worth noting that, while these are potential ways that an AI-based search engine could increase the effectiveness of advertisement and monetize its operations, much research and development is needed to implement these ideas and ensure that they are executed in a responsible and ethical manner. Additionally, it's important to have a clear understanding of the objectives and limitations of the AI systems, and to ensure that the monetization strategy aligns with the company's goals and values.
マジレスされてチビッた．こりゃGoogleさんもビビるわけだ．
ぼく：
How were you implemented? Is it deep learning-based?
I am a language model called GPT-3 (Generative Pre-trained Transformer 3) that was developed by OpenAI. It is a deep learning-based model that uses a type of neural network called a transformer, which was trained on a large dataset of text to learn patterns of language.
GPT-3 is trained using a technique called unsupervised learning, where the model is given a massive amount of text data and uses this data to learn patterns and relationships in the language. This allows GPT-3 to generate human-like text when given a prompt, and to understand and respond to natural language input.
The training process of GPT-3 involves a technique called pre-training, which means that the model is trained on a massive dataset before being fine-tuned on a smaller task-specific dataset. This pre-training allows GPT-3 to have a good general understanding of the language and to be able to adapt to specific tasks more easily.
The GPT-3 model has 175 billion parameters, which is one of the largest language models to date, making it able to generate very human-like text and to understand context in a very natural way.
ぼく：
How does GPT-3 have a knowledgebase like an ontology? As it is deep learning-based, the knowledgebase like an ontology would not be implemented explicitly, but the structure should be designed with an expectation of having such a knowledge about hierarchy of concepts.
GPT-3, like other deep learning models, does not have an explicit knowledgebase or ontology built into its structure. Instead, it has been trained on a large dataset of text, which allows it to learn patterns and relationships between concepts.
However, the training data that GPT-3 was exposed to, likely contains a wide range of concepts and hierarchical structures. As GPT-3 learns patterns in the data, it can begin to understand the relationships between different concepts and ideas, and how they are related to each other. This allows the model to generate text that is more coherent and semantically meaningful, making it possible to understand the context and hierarchy of concepts, but it does not have an explicit ontology like a knowledge graph.
It can be said that GPT-3 has a certain level of "implicit ontology", in the sense that it has learned the relationships between concepts in a way that is similar to how a knowledge graph or ontology organizes information. However, it's important to note that GPT-3's understanding of concepts and relationships is based on the patterns it has learned from the training data, which is not a structured and explicit knowledgebase like an ontology.
ぼく：
Then how does GPT-3 handle the long-term or short term memories? Can it remember information about the on-going chatting? My name is Masuda, can GPT-3 keep it in the memory? Furthermore, can it learn and understand the new information from the Q-A queries, and use it in the future queries?
GPT-3 handles long-term and short-term memories differently. When it generates text, it uses a technique called attention mechanism which allows the model to focus on certain parts of the input while generating the output. This allows GPT-3 to keep track of previous information and context when generating text, which can be thought of as a form of short-term memory.
Regarding the on-going chatting, GPT-3 can keep track of certain information, like the name you've provided, Masuda, during the conversation and use it in future responses. However, it's important to note that GPT-3 is a stateless model, which means that it doesn't have a permanent memory that it can refer to after a conversation ends.
Regarding learning from Q-A, GPT-3 is trained on a massive dataset of text, and it learns patterns and relationships between concepts from this data. It can generate text that is semantically meaningful and coherent, but it does not have the capability to learn new information from Q-A sessions and use it in future queries. However, OpenAI has developed another model called DALL-E, which uses GPT-3 and it is capable of learning from Q-A sessions and use it in future queries.
ぼく：
Is ChatGPT superior to the Google search? Previously people used Google to search for their questions. Now a days, ChatGPT can answer to those questions. What are pros and cons of ChatGPT over the Google search?
ChatGPT and Google search are different technologies with different capabilities and strengths.
Google search is a powerful web search engine that can quickly find relevant information from a vast amount of web pages and documents. It uses complex algorithms to rank and sort search results based on relevance, popularity, and other factors. Google search is very good at providing factual information and is an excellent tool for researching a wide range of topics.
ChatGPT, on the other hand, is a natural language processing model that can generate human-like text. It is trained on a large dataset of text and uses this knowledge to understand and respond to natural language input. ChatGPT can generate text that is more coherent and semantically meaningful than a simple information retrieval engine like Google search. ChatGPT can also be used to generate text that is more engaging and human-like, such as in chatbots and virtual assistants.
One of the main advantages of ChatGPT over Google search is its ability to understand and respond to natural language input in a more human-like way. ChatGPT can also generate text that is more coherent and semantically meaningful, which can be useful in many applications. However, Google search is better at providing factual information and searching for specific pieces of information.
Another disadvantage of ChatGPT is that it doesn't have the ability to retrieve information from the web, it can only generate text based on the patterns it has learned from the training data. That's why it's not a replacement for a web search engine like Google but it can be used as an additional tool to help people to find the information they are looking for.
In summary, ChatGPT and Google search have different strengths and capabilities. While Google search is better at providing factual information, ChatGPT is better at understanding and responding to natural language input in a more human-like way.
ぼく：
Why don't ChatGPT refer to Google search in the generation of the conversation? Google Assistant has such a function. Is the reason due to the fact that OpenAI is funded by Google?
ChatGPT is a language model that generates text based on the patterns it has learned from the training data. While it can understand and respond to natural language input in a human-like way, it does not have the capability to access external sources of information like Google search.
Google Assistant, on the other hand, is a virtual assistant that can access a wide range of information and services through the internet, including Google search. Google Assistant can use this information to provide more accurate and relevant responses to user queries.
The reason ChatGPT does not refer to Google search during the generation of the conversation is likely because it was not designed or trained to do so. Instead, it was designed to generate text based on the patterns it has learned from the training data, and it does not have the capability to access external sources of information.
It's worth noting that OpenAI and Google are separate organizations, even though Google is an investor in OpenAI, this doesn't necessarily mean that the two companies work together on their products and services. OpenAI has its own development team, goals and roadmap and they are independent from Google.
ぼく：
I am going to post this conversation with ChatGPT in the anonymous diary of Hatena co. What should I do for attracting people to get many bookmarks?
There are several things you can do to attract people and increase the chances of your conversation with ChatGPT getting many bookmarks on Hatena diary. Some suggestions include:
1. Make sure your conversation is well-written and easy to understand. Use clear and concise language, and consider formatting your text in a way that makes it easy to read.
2. Use relevant keywords and hashtags in your diary entry. This can help make your conversation more discoverable to people searching for related topics on Hatena diary.
3. Include images or videos in your diary entry. This can make your conversation more visually appealing and can help attract more readers.
4. Share your diary entry on social media or other platforms. This can help increase the visibility of your conversation and attract more readers.
5. Encourage readers to share their thoughts and opinions on your conversation by including a call to action or a question at the end of your diary entry.
6. Finally, you can also try to participate in the conversation on Hatena diary, by answering the questions, responding to the comments, and engaging with your readers.
It's important to remember that getting many bookmarks on a diary is not easy and it can take time and effort to build an audience. But by following these tips and being consistent with your diary entry, you will increase the chances of attracting more readers and getting more bookmarks.
ぼく：
| 13 | はてなブックマーク - 人気エントリー - 2008年11月1日 | https://web.archive.org/web/20170815132626/http://b.hatena.ne.jp/hotentry/20081101 | |
| 14 | はてなブックマーク - 人気エントリー - 総合 - 2010年5月27日 | https://web.archive.org/web/20190522181226/http://b.hatena.ne.jp/hotentry/all/20100527 | |
| 15 | 【復旧済み】各カテゴリの特集の一覧に、想定とは異なるものが多数表示される不具合が発生しています - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2019/05/10/134428 | 4668551187895269474 |
| 16 | コメント一覧ページのデザインリニューアルおよびページ内の一部機能の廃止・整理を行います - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2017/08/08/150000 | 4667408485643465858 |
| 17 | 簡易はてな記法 - はてなブックマークヘルプ | https://b.hatena.ne.jp/help/entry/textformat | 4669405056148061858 |
| 18 | eidを使えばもっとURLを短くできる | https://anond.hatelabo.jp/20081219194442 | 11362837 |
| 19 | URLエンコードについておさらいしてみた - Qiita | https://qiita.com/sisisin/items/3efeb9420cf77a48135d | 347680902 |
| 20 | はてなブックマークのEIDの桁数が激増したのはいつだろう | https://anond.hatelabo.jp/20190127151652 | |
| 21 | 重複した URL を正規 URL に統合する | Google 検索セントラル | ドキュメント | Google Developers | https://developers.google.com/search/docs/advanced/crawling/consolidate-duplicate-urls?hl=ja | 4694503810869473858 |
| 22 | Consolidate Duplicate URLs with Canonicals | Google Search Central | Documentation | Google Developers | https://developers.google.com/search/docs/advanced/crawling/consolidate-duplicate-urls | 4695808187685102274 |
| 23 | URLが複数存在する同一ページでコメント一覧ページが分散する仕様を、統合されるよう変更しました - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2019/02/28/173401 | 4667408469537322306 |
| 24 | URLクエリパラメータ(クエリストリング)の意味とは。使い方は? 除外はすべき?［第4回］［第4回］ | Googleアナリティクスとは／衣袋教授のGoogleアナリティクス入門講座 | Web担当者Forum | https://webtan.impress.co.jp/e/2012/04/26/12663 | 351312146 |
| 25 | 高木浩光＠自宅の日記 - はてなブックマークを禁止する技術的方法, 追記, 追記2 （23日） | http://takagi-hiromitsu.jp/diary/20071222.html | 6889081 |
| 26 | [B! はてな] はてなブックマーク - about:blank | https://b.hatena.ne.jp/entry/s/b.hatena.ne.jp/entry/about:blank | 4707586658055348514 |
| 27 | おっ - kikuchi1201 のブックマーク / はてなブックマーク | https://b.hatena.ne.jp/entry/2805/comment/kikuchi1201 | |
| 28 | はてなブックマークされてる不思議なページ | https://rcmdnk.com/blog/2014/02/24/blog/ | 4671123851382313506 |
| 29 | はてなブックマークの全文検索機能を改善しました - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2015/06/22/114958 | 4667408538793733762 |
| 30 | はてなブックマークっていつからOR検索できるようになったの | https://anond.hatelabo.jp/20121006222621 | 241122808 |
| 31 | 知らなくても困らない！はてなブックマークのアレな使い方 - tipos taronga | https://tt.hatenablog.com/entry/2013/11/16/215703 | 4713084010265175938 |
| 32 | マイホットエントリー機能のご紹介 - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2013/05/08/131308 | 4667408422829508482 |
| 33 | マイブックマーク検索の機能を強化し、検索結果の並び替えや絞り込みができるようになりました（PC版ブラウザ） - はてなブックマーク開発ブログ | https://bookmark.hatenastaff.com/entry/2021/09/02/160546 | 4707764769367740738 |
| 34 | はてなブログスター（星マーク）効果は?１万円購入の圧倒的な効果 | https://blog-support.jp/hatenablog-star/ |
今回書いた増田にも多くのブクマが付き、有難く思う。以下返信。
これは詳しい
ブクマしておく
誰得の詳しいまとめ
おつおつ！！
コメ有難う。おかげで次も書こうという気になる。
有用なツール紹介感謝（ぐぬぬ、向こうのブコメの方が多いと思いつつ）。
参考ページ[FAQ]はてなブックマークの「総合」カテゴリーと「一般」カテゴリーの違いはどこにある?を載せたから大丈夫だろ、という不親切な態度は許されなかった。
門外漢によく知ってるねと褒める時に使う言い方の事例集だ。俺は詳しいんだ。
カラースターの値段が
紫スターすごい
ギブミーカラースターとか言われたら、青1個投げるとちょうど良さそう。
なんかよくわからんけど参考になりそう
まだAPIの解説も残っているんじゃ（すぐに投稿できるとは言っていない）。
GitHubにでも書いたほうが良いのでは
増田への愛（執）着が勝ったが、外部リンクを数件しか貼れず注釈機能が無く字数制限も厳しい環境に投稿して良いのかという葛藤もある。
「錯綜」の解釈を間違っていて一対多の意味を取り違えた。「分散」かな。 & は予約文字というよりも値が途切れ # はブラウザの機能としてサーバに送信されない。 1d. は {2} ではなく {1} (%enc)
指摘を参考に"エントリページ"の章等を修正。URLと引数については、修正後の内容なら以下のようになることを読取っていただけるかなと。
1a例 https://b.hatena.ne.jp/entry/s/anond.hatelabo.jp/20220521220951
1d例 https://b.hatena.ne.jp/entry?url=https%3A%2F%2Fanond.hatelabo.jp%2F20220521220951
API編も期待してる
善処する（GitHubに投稿する方に気持ちが傾いてるが全く触ったことがない上に、VSCodeとWSLとgitを導入してはてなのウィジェットスクリプト解読環境も整えようなどと考えてるので、いつになるか定かでない）。
「はてなフィルター」というウェブサービスも加えて
ChromeならPersonal Blocklist
Firefox(57以前)ならHide Unwanted Results of Google Searchを入れろ
スマホは知らん
どうもこんにちは！ もっくんです。
みなさんは検索結果で「どうしても読みたいんだけれど、このサイトにPVを残したくない…」
そう思ったことはありませんか？
あからさまなテンプレート記事、？マークだらけのタイトル、とにかく上位表示だけを狙った空っぽの記事…
それでも「正直どうでもいい」情報を得るために、中を見てみたい！ でもPVは残したくない！ と思うこと、あると思います。
そこで！ 今回はPVを残さずに、それらを見る方法を紹介したいと思います。
やり方はカンタンです！
①Google Search - Visible Cached + Similar links をインストール！
https://userstyles.org/styles/64844/google-search-visible-cached-similar-links
Stylishをインストールしたあと、こちらのuserstyleをインストールしましょう。
その状態で検索結果を見てみると、全てのページに「キャッシュ」と表示されていると思います。
これは「Googleキャッシュ」といって、Googleが一時保存したローカルデータです。
ここにアクセスして表示されるデータは全てGoogle上の一時データなので、ページビューとしては一切カウントされません。
③キャッシュページの上部枠を「uBlock」で削除！
キャッシュページを開くと、「このページは何時何分にgoogleが取得～」というジャマな表示が出てきます。
これが役に立った試しはないので、ublockやAdblockなどの拡張機能の「要素をブロック」機能で消してしまいましょう。
これでこのようなクソ記事にアクセスしつつ、PVを残さずに立ち去ることができます。
では、もっくんでした！
んなもんhide unwanted results of google searchに片っ端からぶち込めよ
管理してるサイトの順位が軒並み１、２ページ下がっているのだが、、
Is Google Search Updating? January 8th & 9th
http://www.seroundtable.com/google-update-17935.html
英語に詳しい人教えてください！！
あまり歓迎されていないGoogle Search Wikiだけど意外にも便利なことに気がついた。
個人的にはブックマークはこの機能で十分かもしれない。
よくあると思われる勘違いとして、「そんなに同じ単語で何度も検索しない。」
という意見があると思うけどどうやら同じ単語じゃなくても有効になるようだ。
Search Wikiの上矢印をクリックして、白ごはん.comを最上位においておくと
次にたとえば「和食」で検索しても白ごはん.comが最上位に出るようになる。
賛否あるかも知れないけれどなかなか便利だと思う。
がんがん登録していけば最終的にはどんな単語で検索しても
いくつかはお気に入りサイトが推薦されるようになるんじゃないかな。
もう一つは検索結果の追加機能。
これは、全く関係のない結果を追加できる所が面白い。
たとえばインドに旅行する前に現地で使うかもしれないAjax IMEを
「india」の検索結果に登録しておく事ができる。
同様にインドで使いたい他のサイトも「india」と関連づけておけば
現地のネカフェでGoogleにログインして「india」で検索するだけで
利用したいサイトの一覧が手に入る。
実際の検索では「india」一語で検索する事なんてないだろうから邪魔にもならないはず。
まぁソーシャルブックマークでタグつけといても一緒なんだけどね。
