DSIT: 바카라 사이트 site search
바카라 사이트 site search is the search engine for 바카라 사이트. It enables users to search for information and services on 바카라 사이트 by entering a search query to view results that are relevant to their query.
Tier 1 Information
1 - Name
바카라 사이트 site search
2 - Description
바카라 사이트 site search (the search engine on 바카라 사이트) is powered by a Google search product called Google Vertex AI Search. This product uses algorithms to determine which search results are returned, in what order. This allows users to search using natural language queries, queries that reflect the way that people actually speak. 바카라 사이트 is a government website where the majority of available information for public consumption is stored, the site search algorithm provides users a function to search across the entire 바카라 사이트 for the information that is relevant to them and what they need.
3 - Website URL
/ - The search input box is on the homepage of 바카라 사이트 and can be found via the magnifying glass icon drop down on any 바카라 사이트 page.
4 - Contact email
govuk-site-search@digital.cabinet-office.gov.uk
Tier 2 - Owner and Responsibility
1.1 - Organisation or department
바카라 사이트 , The 바카라 사이트 Digital Service
1.2 - Team
바카라 사이트 Site Search Team
1.3 - Senior responsible owner
Deputy Director 바카라 사이트 App and AI
1.4 - External supplier involvement
Yes
1.4.1 - External supplier
Google UK Limited manage Google Vertex AI search that powers 바카라 사이트 site search.
1.4.2 - Companies House Number
03977902
1.4.3 - External supplier role
Google UK Limited manage Google Vertex AI search that powers 바카라 사이트 site search. This means that they are responsible for the maintenance, performance and optimisation of the tool.
1.4.4 - Procurement procedure type
The contract was awarded following a procurement process that went through the Crown Commercial Service바카라 사이트檚 Big data & analytics framework (Lot 2). Following the invitation to tender a call off contract was awarded to Google UK limited in November 2023.
1.4.5 - Data access terms
That data is processed in accordance with GDPR.
That the data shared with Google for the purposes of retrieving and ranking search results shall be used for no other purposes.
Tier 2 - Description and Rationale
2.1 - Detailed description
A user enters their search into the search box on 바카라 사이트. The user바카라 사이트檚 search query (along with other relevant data e.g. user filter selections) is sent to Google Vertex AI search (VAIS) by secure API. VAIS processes the request using models to understand the query바카라 사이트檚 intent, retrieve relevant results, and rank the results. Several factors determine what content should be retrieved and in what order that content should be ranked. Factors such as: keyword matching, content popularity, and semantic similarity. The final ranking is also impacted by rules that 바카라 사이트 have configured in VAIS to define which 바카라 사이트 content types are generally most and least important to users. VAIS sends the results back to 바카라 사이트 via secure API. 바카라 사이트 renders this data on the frontend as search results for the user to view.
2.2 - Scope
바카라 사이트 site search is a search engine product on 바카라 사이트. It exists to make it easy for users to find information, pages and services on 바카라 사이트. It is a public facing product that enables users of 바카라 사이트 to search the content of the 바카라 사이트 website to find pages that are relevant to their 바카라 사이트 visit.
It is only designed to support users to search for content on 바카라 사이트. It does not enable users to search through content on other websites e.g. local government websites or devolved administration websites, although where there are links to this content on 바카라 사이트 it will surface them.
There is a 50 character limit to search requests, queries can be submitted as words, phrases or questions to provide a list of webpages output.
2.3 - Benefit
VAIS generates search results with a high degree of relevance, which is the biggest driver for using this search engine product to power 바카라 사이트 site search.
It enables semantic search: the ability for search engines to 바카라 사이트榰nderstand바카라 사이트� a user바카라 사이트檚 intent when they search for something, and return relevant results. This enables users of 바카라 사이트 site search to search using natural language queries (queries that reflect the way that people actually speak) and get highly relevant results. It is effective at handling misspellings or synonyms - so users do not need to know exact government terminology to get highly relevant results.
2.4 - Previous process
Prior to using VAIS, 바카라 사이트 site search was powered by an open source search engine that had been customised by 바카라 사이트. This customisation included the introduction of a Learning to Rank model that used an algorithm to improve the relevancy of results.
2.5 - Alternatives considered
Other products were considered. Most of these products used some kind of algorithmic ranking, but VAIS was considered to be the product that would be best suited to 바카라 사이트바카라 사이트檚 requirements.
Tier 2 - Decision making Process
3.1 - Process integration
Users engage 바카라 사이트 site search to find government information and services. This is one of the key ways users find information on 바카라 사이트; the others being browsing the site or using external search engines. The site search is designed to speed up the process of users finding the information they need and finding the relevant content first time without having to search multiple pages.
In so far as site search influences users바카라 사이트� decision making, it would be what pages are shown as being relevant for their query, and therefore, worth clicking on. So, for example, if a user searches for 바카라 사이트渁pply for universal credit바카라 사이트�, the top pages that appear in search results are likely to be what a user clicks on (most users click on one of the top three results).
So the ranking of what appears where in search results does impact user decision making. However, other than providing an ordered list of results, 바카라 사이트 site search doesn바카라 사이트檛 do anything else to 바카라 사이트榩ush바카라 사이트� users towards clicking on particular results.
3.2 - Provided information
Site search provides an ordered list of search results with a page title and page description for each result. The human can then decide which web page looks like the potential page they were searching for in the returned list.
3.3 - Frequency and scale of usage
We only collect data on how users interact with search from users that consent to analytics tracking. From this data we can see that there are 3-4 million uses of search each month. The real volume is likely to be higher than this (because of users opting how of analytics tracking).
3.4 - Human decisions and review
Although the order of search results in site search influences the pages that users visit, we can see through analytics data that users do not always click on results. In c. 1 in 4 searches users will refine their search (search more than once by rephrasing their query), and in c. 20% searches users will search but will not click on a result. This behaviour indicates that users are viewing results and making their own decisions about the usefulness of those results.
3.5 - Required training
The development team - The 바카라 사이트 team working on site search has worked closely with the product team at Google to understand, deploy and configure VAIS.
3.6 - Appeals and review
At the bottom of the site search page - as is the case with all pages on 바카라 사이트 - there is a user feedback form so users can share feedback on the site search page.
The 바카라 사이트 have regular interactions with Google to provide them feedback on the Google Vertex AI Search product.
Tier 2 - Tool Specification
4.1.1 - System architecture
Attached
4.1.2 - Phase
Production
4.1.3 - Maintenance
바카라 사이트 runs continuous monitoring on the performance of site search, which includes monitoring the technical performance of the product, and the quality of search results. If any significant degradations in quality are found they are either addressed internally or fed back to VAIS.
4.1.4 - Models
Google Vertex AI search is proprietary technology so we don바카라 사이트檛 have a full list of models that feature in the tool.
At the time of ATRS publication Google Vertex AI search uses the family of Gecko embedding models for the purpose of powering semantic search. The model is based on a neural network architecture.
Tier 2 - Model Specification
4.2.1 - Model name
Google Vertex AI Search
4.2.2 - Model version
2024
4.2.3 - Model task
The model바카라 사이트檚 task is to ingest the user바카라 사이트檚 search query, process it, retrieve documents from 바카라 사이트 data that are relevant to that search query, rank those documents in order of relevance to the user바카라 사이트檚 query, and return data on those documents so that they can be displayed as a list of search results on 바카라 사이트.
4.2.4 - Model input
User search query text, and query parameters i.e. what filters the user has selected
4.2.5 - Model output
A ranked list of search results, and total count of results retrieved
4.2.6 - Model architecture
Google Vertex AI search is proprietary technology so we don바카라 사이트檛 have a full list of models that feature in the tool.
At the time of ATRS publication Google Vertex AI search uses the family of Gecko embedding models for the purpose of powering semantic search. The model is based on a neural network architecture.
4.2.7 - Model performance
The 바카라 사이트 Search team have used a number of metrics to evaluate the performance of the search engine. These metrics include:
Technical metrics on search availability, latency and error rates. Performance metrics on click through rate, position of clicks and judgement list scores.
These metrics enable us to monitor that the VAIS is returning search results to 바카라 사이트, without a perceptible delay for users, and that the results returned are of a high level of relevance.
4.2.8 - Datasets
바카라 사이트 content data: public data on the content that is on 바카라 사이트
Events data: anonymised data from users that have consented to analytics tracking about their interactions with site search.
4.2.9 - Dataset purposes
Events data is used to train the model; to provide signals on what content data is popular with users.
바카라 사이트 content data is the dataset that the model retrieves and ranks to provide relevant search results for user queries.
Tier 2 - Data Specification
4.3.1 - Source data name
바카라 사이트 content data, 바카라 사이트 user event data
4.3.2 - Data modality
Text
4.3.3 - Data description
바카라 사이트 content data is the data of the text of the documents published on 바카라 사이트. Events data is data about how users (that have consented to analytics tracking) interact with 바카라 사이트 site search.
4.3.4 - Data quantities
Content Approximately 697K records of 바카라 사이트 content (15 metadata attributes and unstructured HTML content) in total.
Events Approximately ~70MB/157K records of raw GA4 Search events (7 attributes) and 0.7GB/8M records of raw GA4 View Item events (8 attributes) daily.
4.3.5 - Sensitive attributes
Some 바카라 사이트 content data contains information on people e.g. names and titles, but this is all publicly available.
Google analytics data collected by 바카라 사이트 is anonymised, so events data is not traceable to individuals. 바카라 사이트 redacts query strings that look like personal data, based on pattern matching, to prevent personal data being held by 바카라 사이트 or Google.
4.3.6 - Data completeness and representativeness
We send the majority of 바카라 사이트 content data to VAIS. But there are some document types that we do not send because they are not useful for users in a search engine context e.g. the 바카라 사이트 homepage, or similar navigation pages. A list of these document types ignored can be found here:
Our event data only represents the user behaviour of users that have consented to analytics tracking.
4.3.7 - Source data URL
Content data: Event data is not openly accessible.
4.3.8 - Data collection
Content data is captured when 바카라 사이트 publishers publish, update, and delete content from 바카라 사이트.
Event data is captured by Google Analytics 4 as part of the dataset that 바카라 사이트 collects to improve site performance. No additional events data is captured specifically for search.
4.3.9 - Data cleaning
Content Once content is approved for publishing onto 바카라 사이트 it is added to the 바카라 사이트 Publishing queue where appropriate records are indexed and their attributes corresponding to the 바카라 사이트 Search schema collected for search capabilities.
Events GA4 processed data is filtered for appropriate events and only appropriate attributes are carried forward for import.
4.3.10 - Data sharing agreements
The conditions of the data sharing we do with Google Vertex AI search is covered by the contract 바카라 사이트 has in place with Google for the use of this product.
4.3.11 - Data access and storage
Content The ~697K content records are continually added, updated or deleted from Google바카라 사이트檚 VAIS platform as published via the publishing queue Events Google VAIS requires 90 days of Events data for optimal training/tuning and events data will remain securely stored in the VAIS datastore for training/tuning until after 90 days when they are purged. Quota limits on event storage is 40 billion events per VAIS environment/instance
Tier 2 - Risks, Mitigations and Impact Assessments
5.1 - Impact assessment
Data Protection Impact Assessment was completed and signed off before the migration to Vertex in November 2023. It continues to be updated and reviewed.
5.2 - Risks and mitigations
The key risk for 바카라 사이트 Search is using an algorithmic model for site search whereby that the model doesn바카라 사이트檛 provide relevant results for user search queries. The impact of this risk would be that citizens would be using site search to find information and services on 바카라 사이트, but search results would not reflect the most useful information and services for their query. This could result in time wasted for users if they have to find more relevant information by searching in other ways, or it could mislead users on the action they need to take.
We mitigate this risk by monitoring the relevance of results. We do this through judgement lists where we compare an ideal set of results to the results the search engine is producing. We also monitor user behaviour through metrics like click through rate, and exit rate from search, so we can see quickly if user behaviour is changing as a result of a degradation of search results. If we detect a degradation in results relevance we work with Google to identify the root course and remediate it.