I am reading the Google Photos API documentation. I can't find out what mediaItemId is, see for example here:
https://developers.google.com/photos/library/guides/access-media-items#get-media-item
There are some other questions that might be related, but they have no answers:
How to get mediaItemId of a Google photo using its shared URL?
I've not used the API but I'm familiar with other Google services and am a Photos user.
If you consider you're experience with photos.google.com, you browse a somewhat unstructured list of all your photos. The Photos (phone|browser) apps do categorize photos by date but you have to search to filter by other metadata to find the specific photo(s) that you're seeking. Or you happy-scroll through years of photos of your cat.
This contrasts with another common metaphor for arranging files in which a hierarchy of folders is used to categorize the content e.g. /photos/cats/2022 but this mechanism is limited because you can only really navigate through one dimension (the folders).
Considerable metadata (type, width|height, creation date etc.) is associated with each photo and it is customary in schemas like this to construct a unique ID for each object. The unique ID is sometimes exposed to the end-user but not necessarily. Identifiers are generally for the system's own purposes.
With Photos, there are public, unique identifiers in the form of URLs for each photos but evidently the id and the URL although probably related (perhaps via a hash) aren't obviously related.
So, since it's not always possible to specific a photo uniquely by e.g. "The one of my dog where he's wearing sunglasses because of the eclipse" and the absence of folders, a really powerful alternative (which you'll need to employ) is to search for some subset of the photos and then iterate over the results.
It appears that the Photos service has such a search to which you provide Filters and each of the items in the results will be a MediaItem (uniquely identified by id).
Unlike the file system example above, because Photos does not use a fixed hierarchy, we can view our Photos by filtering them using an extensive set of metadata: photos of cats, taken in 2022, using my phone.
Related
I'm starting an online business targeted at a particular demographic and interests so I would like to produce content targeted at what this particular target market are actually searching for.
Google Ads allowed me to refine my target audience to the exact categories (demographics and interests) I needed but I couldn't tell me what that category of people tend to search for except for the tiny subset that happens to click on one of my ads which is very rare given I am just starting with a small budget. I would like to know the most popular search terms for everyone in the categories I specified not just those who happened to click on my ads.
I tried Google Trends, that told me the popularity of a particular search term for a given country but that's too broad - I need to narrow it down to a particular city, age group, parental status and interests. Google Trends also helped me find popular related search terms given a particular search term so I could try using that to see if there are any common popular related search terms related to my guesses but I could miss terms related to terms I never thought of.
I could try producing content across a rage of topics which I think my target audience might be interested in and then analyse the results using Google Ads but that could be a very expensive trial and error process and I might miss more popular topics which I never thought of.
Of course I could try to ask my target market in person directly (by interrupting people in the street!) but that would be very expensive for me because I would have to travel to and stay at the location where my online business is targeted, hoping to meet people with the exact same demographic and interests that I am looking.
I'm sure there must be a way to figure this out using the the Google search analytics. Essentially, all I need is a list of most popular recent Google search terms for a particular location, demographic and interests group in Google Analytics. Could anyone help me understand how to get this list?
Here are a few considerations, even if you found an answer.
Take a look at the AdRoll platform. Here's a potentially helpful article from them about target audience and demographics.
A recent article about AdWords demographic targeting. An older looking article, connecting demographics to search queries, but page's source code suggests an update this year.
Last but not least, you're probably eligible to talk with a Google Small Business Advisor.
I am interested in implementing a search feature on a website. It is a location search, so address/state/zip all should work. Which will then show results in that area and allow it to be filtered.
My question is:
What's the best approach for something like this?
There are literally dozens of ways of doing this (if not more). The exact implementation would depend on the technology stack that you use, but as a very top level overview:
you'd need to store the things you are searching for somewhere, and tag them with a lat/long location. Often, this would be in a database of some kind.
using a programming language, you would need to write a search that accepts a postcode, translates that to a lat/long and then searches the things in your database based on the distance between the location of the thing, and the location entered in the search.
if you want to support filtering, your search would need to support that too. This is often called "faceting" the search.
Working out the lat/long locations will need to be done using a GeoLocation service, there are some, such as PostCode Anywhere that will do this as a paid service, and others that are free (within reason), such as the Google Maps APIs.
There are probably some hosted services that will do what you want, you'd have to shop around.
Examples of search software that supports geolocation searching out of the box are things like Solr, Azure Search, Lucene and Elastic.
Title says almost everything.
I found that the music "Boom - 2006 Remastered Version" has two different IDs that can be found in the App:
3EKjTDAEIdyQqsA9qtb5P2
0zlAqnRv07p9ezzFf3k2ky
But when using the API to get information about each one, it returns the same ID:
3EKjTDAEIdyQqsA9qtb5P2
Is this a bug?
It is unfortunately not a bug, but it is indeed very annoying, and your code needs to be able to handle it.
"Give me info for track A! Ok, here is info for track B, just like you asked".
It is a legacy thing still left in the Spotify metadata model called track redirects (the some concept exist on albums and artist too, but are less of a problem there). It was made so that we could quickly merge duplicate albums. It means that once upon time, there were two "different" tracks on different albums that were identical. We had lots of them on artists pages for popular artists. Labels would very often upload one album for one country and another identical one for another country instead of just saying that one album was available in two countries. Sometimes by mistake, most often because of cross licensing issues between labels and countries.
Track redirects are quite rare though if you look at the entire catalog. Most of these redirect tracks are only surfaced in old playlists and are for instance never returned in search results or artist pages. These days we never merge duplicates like this, but instead make sure only one is shown on artist pages, etc. and link to the other in case one is unavailable in your country. That is the concept called Track relinking in the docs. https://developer.spotify.com/web-api/track-relinking-guide/
I work at Spotify and bump into this problem every now and then. I want to change this so the tracks and album become just regular duplicates, because it is much easier to reason about, but it will take a while to fix. I guess I can update my answer here in a few years when it is done.
I am basically working on nlp, collecting interest based data from web pages.
I came across this source http://schema.org/ as being helpful in nlp stuff.
I go through the documentation, from which I can see it adds additional tag properties to identify html tag content.
It may help search engine to get specific data as per user query.
it says : Schema.org provides a collection of shared vocabularies webmasters can use to mark up their pages in ways that can be understood by the major search engines: Google, Microsoft, Yandex and Yahoo!
But I don't understand how it can help me being nlp guy? Generally I parse web page content to process and extract data from it. schema.org may help there, but don't know how to utilize it.
Any example or guidance would be appreciable.
Schema.org uses microdata format for representation. People use microdata for text analytics and extracting curated contents. There can be numerous application.
Suppose you want to create news summarization system. So you can use hNews microformats to extract most relevant content and perform summrization onit
Suppose if you have review based search engine, where you want to list products with most positive review. You can use hReview microfomrat to extract the reviews, now perform sentiment analysis on it to identify product has -ve or +ve review
If you want to create skill based resume classifier then extract content with hResume microformat. Which can give you various details like contact (uses the hCard microformat), experience, achievements , related to this work, education , skills/qualifications, affiliations
, publications , performance/skills for performance etc. You can perform classifier on it to classify CVs with particular skillsets
Thought schema.org does not helps directly to nlp guys, it provides platform to perform text processing in better way.
Check out this http://en.wikipedia.org/wiki/Microformat#Specific_microformats to see various mircorformat, same page will give you more details.
Schema.org is something like a vocabulary or ontology to annotate data and here specifically Web pages.
It's a good idea to extract microdata from Web pages but is it really used by Web developper ? I don't think so and I think that the majority of microdata are used by company such as Google or Yahoo.
Finally, you can find data but not a lot and mainly used by a specific type of website.
What do you want to extract and for what type of application ? Because you can probably use another type of data such as DBpedia or Freebase for example.
GoodRelations also supports schema.org. You can annotate your content on the fly from the front-end based on the various domain contexts defined. So, schema.org is very useful for NLP extraction. One can even use it for HATEOS services for hypermedia link relations. Metadata (data about data) for any context is good for content and data in general. Alternatives, include microformats, RDFa, RDFa Lite, etc. The more context you have the better as it will turn your data into smart content and help crawler bots to understand the data. It also leads further into web of data and in helping global queries over resource domains. In long run such approaches will help towards domain adaptation of agents for transfer learning on the web. Pretty much making the web of pages an externalized unit of a massive commonsense knowledge base. They also help advertising agencies understand publisher sites and to better contextualize ad retargeting.
I found a number of similar questions on SO but they are all are either 2+ years old or aren't exactly what I am looking for.
All I would like to do is obtain a list of twitter users whose bio/profile contains certain terms (scientist, democrat, 'dog lover', etc.).
I've considered using a google site search but so far the results are incredibly noisy.
Any suggestions would be much appreciated!
CS
The Twitter API supports a People Search similar to the website's "Find on Twitter" search feature. Although you can not directly search using only profile descriptions, it appears that the description content is used as part of the search space. If you can think of a way to narrow down your results even further by directly searching the returned users' descriptions, you should be able to do what you're looking for. Check out the Twitter API documentation for more info.
Example:
Try searching for "husband father of three", and you get these results, which obviously are returned because of the profile descriptions.
I have used one tool to search twitter profiles using keywords and many advance filters. I love the information which has been provided by the FollowerSearch tool. The information was very specific, which helps me to analyze the public twitter profiles.
One of the best tools for quickly searching among the 800 million public Twitter accounts in the database is FollowerSearch.
With FollowerSearch, you can quickly conduct searches for Twitter influencers and Twitter bios across its massive database of more than 800 million Twitter profiles. You may look for Twitter profiles based on information like their location, line of work, number of followers, etc.
Twitter Influencer Profile Search
A Twitter bios search will assist you in simplifying the process, whether you're looking for influencers or new talent. You can discover Twitter folks who share your interests. Find out exact information on all the accounts whose bios contain your search term.
Identify key accounts and Twitter influencers that have required terms in their Twitter bios.
Look up new and budding talent.
Find Twitter users with similar interests.
Search Twitter profile or Search Twitter bios for any desired term.
I created a tool that does exactly what your looking for. Find70 let's you search for twitter profiles by their twitter bio. In fact, you can set up as many search filters as you want and define your own weighting for each filter. In your example above, you could search for: scientist, democrat, 'dog lover' and it would return all the accounts that have those in the bio. This can be combined with other filters too. Here it is http://www.find70.com/?t=stack