I want to know whether it's possible to filter the url's that are fetched, based on a condition (for example published date or time). I know that we can filter the url's by regex-urlfilter for fetching.
In my case I don't want to index old documents. So, if a document is published before 2017 then, it has to be rejected. Is there any date filter plugin needed or it's already available !
Any help will be appreciated. Thanks in advance.
If you only want to avoid indexing old documents you could write your own IndexingFilter that will check your condition and avoid the indexing of the documents. You don't mention your Nutch version, but assuming that you're using v1 we have a new PR (it will be ready for the next release) that will offer this feature out of the box using JEXL expressions to allow/prevent documents from being indexed.
If you can grab the PR and test it and provide some feedback would be amazing!
You could write your own custom plugin if you want, and you can check the mimetype-filter for something similar to what you want (in this case we apply the filtering based on the mimetype).
Also a warning is in place, at the moment the fetchTime or modifiedTime that Nutch uses are coming from the headers that the webserver sends when the resource is fetched, keep in mind that these values should not be trusted (unless you are 100% sure) because in most cases you'll get wrong dates. NUTCH-1414 proposes a better approach to extracting the publication date from the content of the page, or you can implement your own parser.
Keep in mind that with this approach you still fetch/parse the old documents you'll just skip the indexing step.
Related
Scenario:
I'm doing some HTML information extraction using a crawler. Right now, most the rules for extraction are hardcoded (not the tags or things like that, but loops, nested elements, etc.)
For instance, one common task is as follows:
Obtain table with ID X. If it doesn't exists there may be additional mechanisms so find the info which are triggered
Find a row which contains some info. Usually the match is a regexp against an specific column.
Retrieve the data in a different column (usually marked in the td, or previously detected in the header)
The way I'm currently doing so is:
Query to get the body of first table with id X (X is in config file). Some websites of my list are buggy and duplicate that id on elements different than table -.-
Iterate over interesting cells, executing regexp on cell.text() (regexp is in config file)
Get the parent row of the matching cells, and obtain the cell I need from the row (identifier of the row is in config file)
Having all this hardcoded for the most part (except column names, table ids, etc) gives me the benefit or being easy to implement and more efficiency than a generic parser, however, it is less configurable, and some changes in the target websites force me to deal with code, which makes it harder to delegate the task.
Question
Is there any language (preferably with a java implementation available) which allows to consistently define rules for extractions like those? I'm using css-style selectors for some tasks, but others are not so simple, so my best guess is that there must be something extending that that a non-programmer maintainer to add/modify rules on demand.
I would accept a Nutch-based answer, if there's one, as we're studying migrating our crawlers to nutch, although, I'd prefer a generic java solution.
I was thinking about writing a Parser generator and create my own set of rules to allow users/maintainers to generate parsers, but it really feels like reinventing the wheel for no reason.
I'm doing something somewhat similar - not exactly what you're searching for, but maybe you can get some ideas.
First the crawling part:
I'm using Scrapy on Python 3.7.
For my project, that brought the advantage, that it's very flexible and an easy crawling framework to build upon. Things like delays between requests, HTTP header language etc. can mostly be configured.
For the information extraction part and rules:
In my last generation of crawler (I'm now working on the 3rd gen, the 2nd one is still running but not as scalable) I've used JSON files to enter the XPath / CSS rules for every page. So on starting my crawler, I've loaded the JSON file for one specific page that is currently being crawled and a generic crawler, knew what to extract based on the loaded JSON file.
This approach isn't easily scalable since one config file per domain has to be created.
Currently, I'm still using Scrapy, with a starting list of 700 Domains to crawl and the crawler is now only responsible for downloading the whole website as HTML files.
These are being stored in tar archives by a shell script.
Afterward, a Python script is going through all members of the shell script and analyzing the content for the information I'm looking to extract.
Here, as you said, it's a bit like re-inventing the wheel or writing a wrapper around an existing library.
In Python, one can use BeautifulSoup for removing all tags like script and style etc.
Then you can extract for instance all text.
Or you'd focus first on tables only, extract all tables into dicts and can then analyze with regex or similar.
There are libraries like DragNet for boilerplate removal.
And there are some specific approaches on how to extract table structured information.
I am stuck on a project at work that I do not think is really possible and I am wondering if someone can confirm my belief that it isn't possible or at least give me new options to look at.
We are doing a project for a client that involved a mass download of files from a server (easily did with ftp4j and document name list), but now we need to sort through the data from the server. The client is doing work in Contracts and wants us to pull out relevant information such as: Licensor, Licensee, Product, Agreement date, termination date, royalties, restrictions.
Since the documents are completely unstandardized, is that even possible to do? I can imagine loading in the files and searching it but I would have no idea how to pull out information from a paragraph such as the licensor and restrictions on the agreement. These are not hashes but instead are just long contracts. Even if I were to search for 'Licensor' it will come up in the document multiple times. The documents aren't even in a consistent file format. Some are PDF, some are text, some are html, and I've even seen some that were as bad as being a scanned image in a pdf.
My boss keeps pushing for me to work on this project but I feel as if I am out of options. I primarily do web and mobile so big data is really not my strong area. Does this sound possible to do in a reasonable amount of time? (We're talking about at the very minimum 1000 documents). I have been working on this in Java.
I'll do my best to give you some information, as this is not my area of expertise. I would highly consider writing a script that identifies the type of file you are dealing with, and then calls the appropriate parsing methods to handle what you are looking for.
Since you are dealing with big data, python could be pretty useful. Javascript would be my next choice.
If your overall code is written in Java, it should be very portable and flexible no matter which one you choose. Using a regex or a specific string search would be a good way to approach this;
If you are concerned only with Licensor followed by a name, you could identify the format of that particular instance and search for something similar using the regex you create. This can be extrapolated to other instances of searching.
For getting text from an image, try using the API's on this page:
How to read images using Java API?
Scanned Image to Readable Text
For text from a PDF:
https://www.idrsolutions.com/how-to-search-a-pdf-file-for-text/
Also, PDF is just text, so you should be able to search through it using a regex most likely. That would be my method of attack, or possibly using string.split() and make a string buffer that you can append to.
For text from HTML doc:
Here is a cool HTML parser library: http://jericho.htmlparser.net/docs/index.html
A resource that teaches how to remove HTML tags and get the good stuff: http://www.rgagnon.com/javadetails/java-0424.html
If you need anything else, let me know. I'll do my best to find it!
Apache tika can extract plain text from almost any commonly used file format.
But with the situation you describe, you would still need to analyze the text as in "natural language recognition". Thats a field where; despite some advances have been made (by dedicated research teams, spending many person years!); computers still fail pretty bad (heck even humans fail at it, sometimes).
With the number of documents you mentioned (1000's), hire a temp worker and have them sorted/tagged by human brain power. It will be cheaper and you will have less misclassifications.
You can use tika for text extraction. If there is a fixed pattern, you can extract information using regex or xpath queries. Other solution is to use Solr as shown in this video.You don't need solr but watch the video to get idea.
I am completely lost.
I think I am definitely missing something fundamental here. Everybody has such awesome stuff to say about Solr but I fail to see it.
I indexed a structured pdf document in Solr.
The problem is when I search for a simple string - I get the entire content field as the response!
I don't know how to change that.
My requirement is that, lets say I search for "metadata"
it should give me
"MetadataDiscussion . . . 4 matches
... make sure that Tika users have a chance to get to all of the metadata created and/or extracted by Tika. == Original Problem == The original inspiration for this page was a Tika ...
10.7k - rev: 2 (current)
last modified: 2010-08-02 18:09:45
"
But it gives me the whole document!- the entire string that was indexed.
It seems like Lucene can only tell me in which field it occurred, not where in the field it occurred
Any help will be greatly appreciated!!
Lucene/Solr is primarily a retrieval engine - it retrieves documents that match a query. So this behavior is desirable and expected. Now as for your requirement, you can use the highlighting feature of Solr to give you exactly that. Suppose your document text is stored in a field named text - then you would pass the following parameters to Solr:
&hl=true&hl.fl=text&hl.snippets=5&hl.fragsize=200
Look through the other parameters to customize it even further.
Solr is amazing :)
I want to do some development in Java. I'd like to be able to access a website, say for example
www.chipotle.com
On the top right, they have a place where you can enter in your zip code and it will give you all of the nearest locations. The program will just have an empty box for user input for their zip code, and it will query the actual chipotle server to retrieve the nearest locations. How do I do that, and also how is the data I receive stored?
This will probably be a followup question as to what methods I should use to parse the data.
Thanks!
First you need to know the parameters needed to execute the query and the URL which these parameters should be submitted to (the action attribute of the form). With that, your application will have to do an HTTP request to the URL, with your own parameters (possibly only the zip code). Finally parse the answer.
This can be done with standard Java API classes, but it won't be very robust. A better solution would be HttpClient. Here are some examples.
This will probably be a followup question as to what methods I should use to parse the data.
It very much depends on what the website actually returns.
If it returns static HTML, use an regular (strict) or permissive HTML parser should be used.
If it returns dynamic HTML (i.e. HTML with embedded Javascript) you may need to use something that evaluates the Javascript as part of the content extraction process.
There may also be a web API designed for programs (like yours) to use. Such an API would typically return the results as XML or JSON so that you don't have to scrape the results out of an HTML document.
Before you go any further you should check the Terms of Service for the site. Do they say anything about what you are proposing to do?
A lot of sites DO NOT WANT people to scrape their content or provide wrappers for their services. For instance, if they get income from ads shown on their site, what you are proposing to do could result in a diversion of visitors to their site and a resulting loss of potential or actual income.
If you don't respect a website's ToS, you could be on the receiving end of lawyers letters ... or worse. In addition, they could already be using technical means to make life difficult for people to scrape their service.
I am new to IR techniques.
I looking for a Java based API or tool that does the following.
Download the given set of URLs
Extract the tokens
Remove the stop words
Perform Stemming
Create Inverted Index
Calculate the TF-IDF
Kindly let me know how can Lucene be helpful to me.
Regards
Yuvi
You could try the Word Vector Tool - it's been a while since the latest release, but it works fine here. It should be able to perform all of the steps you mention. I've never used the crawler part myself, however.
Actually, TF-IDF is a score given to a term in a document, rather than the whole document.
If you just want the TF-IDFs per term in document, maybe use this method, without ever touching Lucene.
If you want to create a search engine, you need to do a bit more (such as extracting text from the given URLs, whose corresponding documents would probably not contain raw text). If this is the case, consider using Solr.