Week 4: Day 2 of Work Experience at LIT
Week 4
Day 2 of Work Experience at LIT
Started 9:00 am, checked email, reviewed yesterdays work and plan for today.
Completed audio and screen-capture recordings. Completed edits of these. Added transitions and effects to video. Added blurs. Next is to add zooms.
From the "self-enrolment video" of last week. On reflection, I also increased the clip-speed of the log in step at the start of the video. Then, converted into MP4.
I read some articles related to IT and design. One of interest is from "Search Engine Watch," on "how RankBrain Does (and Doesn't) Impact SEO."
The main points about RankBrain are that it:
It is based on principles and processes of:
Its purpose is to help Google provide more accurate results and an overall better search experience for users, satisfying their queries.
As opposed to Panda and Penguin for example, RankBrain is an interpretation model, that can't be optimized specifically. As a resolution, the article suggests some SEO practices that are relevant to today:
The future for RankBrain:
It is expected that RankBrain will improve at understanding semantics and concepts and relationships between topics and queries. This would benefit traditional search results pages and now cards and the more recent, voice search query accuracy.
Day 2 of Work Experience at LIT
Started 9:00 am, checked email, reviewed yesterdays work and plan for today.
Completed audio and screen-capture recordings. Completed edits of these. Added transitions and effects to video. Added blurs. Next is to add zooms.
From the "self-enrolment video" of last week. On reflection, I also increased the clip-speed of the log in step at the start of the video. Then, converted into MP4.
I read some articles related to IT and design. One of interest is from "Search Engine Watch," on "how RankBrain Does (and Doesn't) Impact SEO."
The main points about RankBrain are that it:
- Interprets the user query
- Determines search intent
- Selects results (items) from the databases
It is based on principles and processes of:
- machine learning
- association rule learning
Its purpose is to help Google provide more accurate results and an overall better search experience for users, satisfying their queries.
As opposed to Panda and Penguin for example, RankBrain is an interpretation model, that can't be optimized specifically. As a resolution, the article suggests some SEO practices that are relevant to today:
- Doorway pages are dead: instead of a focus keyword, keyword matrices and user experience are to be emphasized.
- Different queries = Different weighting factors: anticipated here is that deviations from standard best practices will be needed.
- Internal linking structures: the adding of internal links to improve user experience.
The future for RankBrain:
It is expected that RankBrain will improve at understanding semantics and concepts and relationships between topics and queries. This would benefit traditional search results pages and now cards and the more recent, voice search query accuracy.
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