In it's current version, is it possible to use Bing's "Narrow By Date" feature when accessing it's API?
I cannot find any information about how to narrow the results such that it only shows results from the "past 24 hours" or "past week" (and so on).
The website/documentation isn't exactly clear on what I can and cannot do, and how. Do any of you know whether it's possible or not?
I can see on their Advanced Search Keywords page that you can use other narrowing features (region, language, hasfeed, etc.) here: http://onlinehelp.microsoft.com/en-ca/bing/ff808421.aspx
If you need any more context or information please ask. Thank you for your patience and help.
The Bing search API is pretty vague in terms of limiting results and what you can and cannot use. After testing various words and placement to try and get date to work, I'm fairly certain that there is not a way to use a date to narrow results.
Related
I am now doing an NLP project which needs some resources from twitter.
I want to get those tweets posted by "real people" instead of any kind of "official accounts", including celebrities, ads, institutions, media, etc. such as #CNN #TodayWeather #obama #DailySale #BestPrice #FashionTrend.
Hence, is there a better way to do so?
I have considered about it for a long time. By using twitter's API, the returned JSON includes a key called "verified". This can be used to detect weather an account is that kind of "official account". However, today, this blue "V" tick is not only for those shining celebrities. Anyone can apply for it as long as they are a real person. So, I think using this solution will rule out a lot of precious resources.
Moreover, I also considered using textual spam filter. yeah, of course, they are quite good in most cases. However, some accounts, such as #FT, their posts never sound like a spammy ad. But it is not what I want.
I want to ask for a better solution. It can be a long term solution, such as using NLP and NeuroNets to learn from labels. But, well, a prompt solution will be very welcomed.
THX
I know that google used to provide a service some time back where you could enter a keyword and google would tell you how many searches have been made using the exact and related keywords. This was a very useful feature while performing SEO(Search Engine Optimization). However I cannot find that particular tool anywhere. Has the service been discontinued? If yes, then what are the alternatives?
It has been replaced by the 'Keyword Planner:
https://adwords.google.com/o/KeywordTool
Some of the options are different, but you cans till get keyword and number of searched from it.
I'd like to get a big list (say 1,000 or more) of word phrases that people search for on the internet recently (anything from the most recent month or week or day is ok). Results from Google or any of the bigger search sites would be okay. And is there a way to do this programmatically? Python would be first choice, shell scripts works too. Thanks!
Bonus points for historical results too.
http://www.google.com/trends
google is pretty data friendly
they even provide rss feeds
http://www.google.com/trends/hottrends/atom/hourly
Yes, It's python friendly with API and easy_install to boot!
http://pypi.python.org/pypi/pyGTrends/0.81
Along with what TelsaBoil post, Google Insights looks to give historical results too
http://www.google.com/insights/search/
I think you should check this ones:
http://www.google.com/trends/hottrends
http://www.google.com/trends/hottrends/atom/hourly [RSS Hourly Feed]
http://pypi.python.org/pypi/pyGTrends/0.81 [Python Google Trends Information Retrieval]
Basically I'm looking for a search engine that searches through a given database. The content will be text being searched.
You will probably want to use a service such as Solr. The easiest way to get started using it is to find a 'cloud' based version, such as Websolr. However, the solution will depend on what language you wish to use when programming your site.
Solutions depend somewhat on language:
1. For java/c#, you have lucene/solr
2. for python you have haystack
You could do text search in the DB directly via LIKE/ILIKE, but the performance depends on DB.
Iconfinder was coded specifically for icon search and at the time (launched in 2007) there were no scripts that worked well for this.
Building a search engine like Iconfinder is not rocket science. I think the hardest part is getting the SQL tuned and figure out how to rank the content. At the moment I collect data about impressions and downloads and calculate a value from that. The icons' rank is based on this value (download/impression) and how well keywords match the tags for the given icon.
Let's say I'm just wondering around with my cellphone and I want to know exactly which place of business I'm in. This would seem to be easy, but I don't see away to do it. It's possible to reverse geocode but this gives an address range. Google doesn't seem to have http base local search using local information, because you could kind of guess from the local search or points of interest. It needs to be through an http API, not an ajax driven map. Is there a way to do this?
You might look at GeoAPI, which lets you search for businesses near a particular lat/lon coordinate and returns detailed information about the business (name, type, hours, etc.). It's a simple JSON API with good documentation and examples.
There's likely more APIs out there for local business data -- which I personally would love to hear about if people want to add them as answers to this question or comments on my answer. What's your favorite? What are the advantages and disadvantages?