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I'm writing a small helper utility for obscure software that is used at a local shop. Basically, I would like to know if anyone searches for anything associated with that software and if publishing my work on the Internet would make any sense. I entered the name of the software into Google Trends, but my terms "do not have enough search volume to show graphs" despite the fact that Google lists 250,000 results for the software name, or 35,000 if I explicitly remove terms such as serial and warez from the search.
Does anyone know of alternatives to Google Trends? Or of another way to find out if people search for a particular keyword?
I found what I was looking for.
Google AdWords Keyword Tool
Yahoo Clues is a service similar to Google Trends. But I don't think it's as effective for any category that is non-entertainment.
If you don't get an answer here, another place to ask might be The Business of Software.
Google Trends was also telling me there wasn't enough data for my query. I found Google Insights to do job nicely. And unlike the AdWords tool mentioned in the author's answer, it actually shows a trend.
Here's an example which shows the emergence of 3 terms with too low of volume to show up on Trends: #bigdata, #datascientist & #datajournalism.
Here's a related SO question.
Related
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I'm pretty new on search engines and pretty newbie on machine learning. But I wanted to know if there is a way to combine functionalities of search engines like elasticsearch or Apache Solr and machine learning project like Apache Mahout, H2O or PredictionIO.
For exemple, if you work on a travel website where you can search for a destination. You start type "au", so the first suggestions are "AUstria", "AUstralia", "mAUrice island", "mAUritania"... etc... This is typically what elasticsearch can do.
But you know that this user has already travelled on Mauritania three times, so you want that Mauritania goes on the first place of suggestions. And I guess that's typically what machine learning can do.
Is there bridges between this two type of technologies ? Can machine learning ensure the work of search engine efficiently ?
I'm open to all answers, regardless of the technologies used. If you have ever experienced this type of problems, my ears are wide open :-)
Thank you
Your question is very general in nature- so my answer will have to be the same.
Consider a recommender framework such as the one in Apache Mahout correlated co-occurance. Unlike the vanilla spark recommender, this implementation allows for multiple types of actions, such as viewed a web site, booked a trip their before, demographic information, etc.
Now you would calculate the recommendations for each user at whatever interval. Recommendations being based on multiple criteria and what other people similar to this user has done. Consider your 'items' in this case to be every destination in the world. So we now have every possible destination ranked for each user.
It is then a trivial extension to index elastic search by user/the ordered list of that users recommended destinations.
For example, we have a user who has visited Berlin, looked at several hotels in Vienna, and is from Romainia. When the user types in "au", we would expect to see "Austria" come up in the results much higher than 'Austrailia'
Per the comments and down votes- you probably should have either A) asked a more specific programming question or B) asked this question on another forum such as Data Science Stack Exchange, fyi
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I wanted to know that sometimes when I search for something on google it shows some results(website links), but it also shows some important links on that website.
I wanted to know that is it a feature of the website or Google uses something to find those main links of the website? Is it related to search engine optimization?
You probably mean Google’s sitelinks.
We only show sitelinks for results when we think they'll be useful to the user. If the structure of your site doesn't allow our algorithms to find good sitelinks, or we don't think that the sitelinks for your site are relevant for the user's query, we won't show them.
(See this [closed] question.)
It has to do with click-through rates of those links. For example, Googling 'Amazon' brings up amazon.com, with a handful of links below: Books, Kindle e-Books, Music, etc.
These are obviously popular categories on Amazon, and Google tracks where users click, then uses that data to make serps more relevant.
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I'm thinking about joining a free software project in order to increase my knowledge of how this kind of projects works, colaborating with people that I dont know (so far), and my C/C++ skills.
I`ve searched on sourceforge and so on, looking for projects that need developers... so my question is: how to join a existing project? (and find one I like)
Pick one you like/are interested in, look over its bug tracker, and contribute patches. As you demonstrate your ability to work along with the developers, you will generally be offered greater involvement (e.g. direct commit access).
#geekosaur has some good points. (+1)
If those don't work, I would consider looking for the lead developer of a project (preferably one with decent activity and leadership) and asking what areas they would like assistance in.
I promise you, almost every open source project manager would absolutely welcome a fresh face to the team!
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My aim is to build an aggregrator of news feeds and blog feeds so as to make
searching/tracking of entitites in it easy. I have been looking at many solutions out there like Terrier, Lucene, SWISH-E, etc.
Basically, I could find only 2 sources of comparison studies done on these engines and one of them is kinda outdated. Basically I want a search engine which would be used in a case in which the data size is not too large, but the indexing will be frequent, every 30 minutes or so. I feel Terrier is not a good tool to be used in this case. It works better when the data size is large and updation frequency is low. Can somebody who has worked in the Information Retrieval field offer some advice ?
Lucene is well known and supported, so personally, that would be my first choice.
If you find a ready-to-use search engine, check out fastcatsearch.
It has been developed for commercial search, and applied to a lot of various sites.
Faster than lucene, and has web-based web manager to use easily.
Hosted in github, and check it out. https://github.com/fastcatgroup/fastcatsearch
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How do i come up with a good name for a website or software I am developing. Are there references for naming websites or software?
think of a rude word to use as an acronym, and then fit in the words to make that acronym fit.
SHAFTED was the code name of one internal project I was working on
Shipment
Help
And
Full
Tracking of
Export
Documentation
OTIS was the clean version I used around managers (Order Tracking Information System)
I let my creativity flow and write up 5-10 names.
Then i google them.If one of them is not in use, i take it. :)
I want to be the names unique ;)
Personally? I don't, they're all horrible. But after a couple days of working on the project it's just a group of letters that means "work left to do," regardless of what I called it. :)
Here is an idea from Paul Graham's Why Smart People Have Bad Ideas essay,
[4] I wrote a program to generate all
the combinations of "Web" plus a three
letter word. I learned from this that
most three letter words are bad:
Webpig, Webdog, Webfat, Webzit,
Webfug. But one of them was Webvia; I
swapped them to make Viaweb.