Lawyers & Attorneys Website Data Scraping Services

There are so many instances where one end’s up needing information from lawyers or bar associations. However, if you approach them directly or look for other ways to get information it might either be difficult or you might not get the information you are looking for. Thus, the best way to go about the scraping lawyer data.

Scraping lawyer data allow you to get information from various attorney websites, bar association websites, or other related websites. Using web scraping tools for getting such information makes it much easier to get all the relevant and important information without actually having to worry about the same.

If you wish to scrape data from lawyer, you are entitled to information such as lawyer name, firm names, address, contact details, history about the lawyers, educational qualifications, the bar association they are part of and much more.

Scraping lawyer data ensure that you also have images of the lawyer you are concentrating on. The result of scrape data form lawyer can be obtained in any format the user wants such as csv, excel, MySql etc. Scraping lawyer data also ensures that none of the information provided are repetitive or redundant.

If you are in need of information regarding any lawyer such as their contact details, address etc. it could end up being a huge and difficult task to get it manually or physically. Thus, taking off the help of scraping tools would ensure that you get all the needed information without actually having to bother about anything at all. The presence of lots of attorney websites and the fact that more and more lawyers are moving to the internet makes getting information easy with the help of some great tools. Scraping data is a very useful and handy method in which one can get all the required and relevant information and that too in a very easy to read format, which makes the method even worthier.

There are quite a few tools or services that you can take help of to get lawyers data scraped. Most of these services also provide with a sample demo and that free of cost. From the sample one can decide if they wish to continue with the services or try some other services. Thus, if you want any information from attorney websites or information about any lawyers, data scraping is a great way to get the same.

Source: https://3idatascraping.wordpress.com/2014/03/18/lawyers-attorneys-website-data-scraping-services/

Benefits of Scraping Data from Real Estate Website

With so much of growth in the recent times in real estate industry, it is likely that companies would want to create something different or use another method, so as to get desired benefits. Thus, it is best to go with the technological advancements and create real estate websites to get an edge over others in the industry. And to get all the information regarding website content, one can opt for real estate data scraping methods.

About real estate website scraping

Internet has become an important part of our daily lives and in industry marketing procedures too. With the use of website scraping one can easily scrape real estate listing from various websites. One just needs the help of experts and with proper software and tools; they can easily collect all the relevant real estate data from the required real estate websites and make a structured file containing the information. With internet becoming a valid platform for information and data submitted by numerous sources from around the globe, it is necessary to gather them all in one place for companies. In this way, the company can know what it lacks and work upon their strategies so as to gain profit and get to the top of the business world by taking one step at a time.

Uses of real estate website scraping

With proper use of website scraping one can collect and scrape the real estate listings which can help the company in the real estate market area. One can draw the attention of potential customers by designing the company strategies in such a way as contemplating the changing trends in the real estate global arena. All this is done with the help of the data collected from various real estate websites. With the help of proper website, one can collect the data and these get updated whenever new information gets into the web portal. In this way the company is kept updated about the various changes happening around the global market and thus, ensure in making plans regarding the company. This way one can plan ahead and take steps that can lead to the company gaining profits in future.

Thus, with the help of proper real estate website scraping one can be sure of getting all the information regarding real estate market. This way one can work upon making the company move as per the market trends and get a stronghold in real estate business.

Source: https://3idatascraping.wordpress.com/2013/09/25/benefit-of-scraping-data-from-real-estate-website/

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it
into a database.

Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

Hard-Scraped Hardwood Flooring: Restoration of History

Throughout History hardwood flooring has undergone dramatic changes from the meticulous hard-scraped hardwood polished floors of majestic plantations of the Deep South, to modern day technology providing maintenance free wood flooring designed for comfort and appearance. The hand-scraped hardwood floors of the South, depicted charm with old rustic nature and character that was often associated with this time era. To date, hand-scraped hardwood flooring is being revitalized and used in up-scale homes and places of businesses to restore the old country charm that once faded into oblivion.

As the name implies, hand-scraped flooring involves the retexturing the top layer of flooring material by various methods in an attempts to mimic the rustic appearance of flooring in yesteryears. Depending on the degree of texture required, hand scraping hardwood material is often accomplished by highly skilled craftsmen with specialized tools and years of experience perfecting this procedure. When properly done, hand-scraped hardwood floors add texture, richness and uniqueness not offered in any similar hardwood flooring product.

Rooted with history, these types of floors are available in finished or unfinished surfaces. The majority of the individuals selecting hand-scraped hardwood flooring elect a prefinished floor to reduce costs per square foot in installation and finishing labor charges, allowing for budget guidelines to bend, not break. As expected, hand-scraped flooring is expensive and depending on the grade and finish selected, can range from $15-40$ per square foot and beyond for material only. Preparation of the material is labor intensive adding to the overall cost per square foot dramatically. Recommended professional installation can and often does increase the cost per square foot as well, placing this method of hardwood flooring well out of reach of the average hardwood floor purchaser.

With numerous selections of hand-scraped finishes available, each finish is designed to bring out a different appearance making it a one-of-a-kind work of art. These numerous finish selections include:

• Time worn aged, dark coloring stain application bringing out grain characteristics

• Wire brushed, providing a highlighted "grainy" effect with obvious rough texture

• Hand sculpted, smoother distressed uniform appearance

• French Bleed, staining of edges and side joints with a much darker stain to give a bleeding effect to the wood

• Hand Hewn or Rough Sawn, with visible and noticeable saw marks

Regardless of the selection made, scraped flooring cannot be compared to any other available flooring material based on durability, strength and visual appearance. Limited by only the imagination and creativity, several wood species can be used to create unusual floor patterns, highlighting main focal points of personal libraries and art collections.

The precise process utilized in the creation of scraped floors projects a custom look with deep color and subtle warm highlights. With radiant natural light reflecting off this type of floor, the effect of beauty and depth is radiated in a fashion that fills the room with solitude and serenity encompassing all that enter. Hand-scraped hardwood floors speak of the past, a time of decent, a time or war and ambiguity towards other races and the blood- shed so that all men could be treated as equals. More than exquisite flooring, hand-scraped hardwood flooring is the restoration of History.

Source: http://ezinearticles.com/?Hard-Scraped-Hardwood-Flooring:-Restoration-of-History&id=6333218

What is HTML Scraping and how it works

There are many reasons why there may be a requirement to pull data or information from other sites, and usually the process begins after checking whether the site has an official API. There are very few people who are aware about the presence of structured data that is supported by every website automatically. We are basically talking about pulling data right from the HTML, also referred to as HTML scraping. This is an awesome way of gleaning data and information from third party websites.

Any webpage content that can be viewed can be scraped without any trouble. If there is any way provided by the website to the browser of the visitor to download content and use the same in a highly structured manner, in that case, accessing of the content programmatically is possible. HTML scraping works in an amazing manner.

Before indulging in HTML scraping, one can inspect the browser for network traffic. Site owners have a couple of tricks up their sleeve to thwart this access, but majority of them can be worked around.

Before moving on to how HTML scraping works, we must understand the reasons behind the same. Why is scraping needed? Once you get a satisfactory answer to this question, you can start looking for RSS or API feeds or various other traditional structured data forms. It is significant to understand that when compared with APIs, websites are more significant.

The most important advantage of the same is the maintenance of their websites where a lot of visitors visit rather than safeguarding structured data feeds. With Tweeter, the same has been publicly seen when it clamps down on the developer ecosystem. Many times, API feeds change or move without any prior warning. Many times, it can also be a deliberate attempt, but mostly, such issues or problems erupt as there is no authority or an organization that maintains or takes care of the structured data. It is rarely noticed, if the same gets severely mangled or goes offline. In case the website has certain issues or the website no longer works, the problem is more in the form of a ball in your court requiring dealing with the same without losing any time. api-comic-image

Rate limiting is another factor that needs a lot of thinking and in case of public websites, it virtually doesn’t exist. Besides some occasional sign up pages or captchas, many business websites fail to create and built defenses against any unwarranted automated access. Many times, a single website can be scraped for four hours straight without anyone noticing. There are chances that you would not be viewed under DDOS attack unless concurrent requests are being made by you. You will be seen just as an avid visitor or an enthusiast in the logs, that too, in case anyone is looking.

Another factor in HTML scraping is that one can easily access any website anonymously. Behavior tracking can be done with a few ways by the administrator of the website and this turns out to be beneficial if you want to privately gather the data. Many times, registration is imperative with APIs in order to get key and with any request being sent, this key also needs to be sent. But, in case of simple and straightforward HTTP requests, the visitor can stay anonymous besides cookies and IP address, which can again be spoofed.

The availability of HTML scraping is universal and there is no need to wait for the opening of the site for an API or for contacting anyone in the organization. One simply needs to spend some time and browse websites at a leisurely pace until the data you want is available and then find out the basic patterns to access the same.

Now you need to don a hat of a professional scraper and simply dive in. Initially, it may take some time to work up figuring out the way the data have been structured and the way it can be accessed just as we read APIs. If there is no documentation unlike APIs, you need to be a little more smart about it and use clever tricks.

Some of the most used tricks are

Data Fetching

The first thing that is required is data fetching. Find endpoints to begin with, that is the URLs that can help in returning the data that is required. If you are pretty sure about the data and the way it should be structured so as to match your requirements, you will require a particular subset for the same and later you can indulge in site browsing using the navigation tools.

GET Parameter

The URLs must be paid attention to and see the way it changes as you indulge in clicking between the sections and the way they divide into various subsections. Before starting, the other option that can be used is to straight away go to the search functionality of the site. Certain terms can be typed and the URL needs to be focused again for watching the changes on the basis of what is being searched. A GET parameter will be probably seen like q which changes on the basis of the search term used by you. Other GET parameters that are not being used can be removed from the URL until only the ones that are needed are left for data loading. Before a query string, there must always be a “?” beginning.

Now the time has come when you would have started to come across the data that you would like to see and want to access, but sometimes, there may be certain pagination issues that require to be dealt with. Due to these issues, you may not be able to see the data in its entirety. Single requests are kept away by many APIs as well from database slamming. Many times, clicking the next page can add some offset parameter that helps in data visibility on the page. All these steps will help you succeed in HTML scraping.

Source: https://www.promptcloud.com/blog/what-is-html-scraping-and-how-it-works/

The Nasty Problem with Scraping Results from the Engines

One theme that I've been concerned with this week centers around data transparency in the search engine world. Search engines provide information that is critical to the business of optimizing and growing a business on the web, yet barriers to this data currently force many companies to use methods of data extraction that violate the search engines' terms of service.

Specifically, we're talking about two pieces of information that no large-scale, successful web operation should be without. These include rankings (the position of their site(s) vs. their competitors) for important keywords and link data (currently provided most accurately through Yahoo!, but also available through MSN and in lower quality formats from Google).

Why do marketers and businesses need this data so badly? First we'll look at rankings:

•    For large sites in particular, rankings across the board will go up or down based on their actions and the actions of their competition. Any serious company who fails to monitor tweaks to their site, public relations, press and optimization tactics in this way will lose out to competitors who do track this data and, thus, can make intelligent business decisions based on it.

•    Rankings provide a benchmark that helps companies estimate their global reach in the search results and make predictions about whether certain areas of extension or growth make logical sense. If a company must decide on how to expand their content or what new keywords to target or even if they can compete in new markets, the business intelligence that can be extracted from large swaths of ranking data is critical.

•    Rankings can be mapped directly to traffic, allowing companies to consider advertising, extending their reach or forming partnerships

And, on the link data side:

•    Temporal link information allows marketers to see what effects certain link building, public relations and press efforts have on a site's link profile. Although some of this data is available through referring links in analytics programs, many folks are much more interested in the links that search engines know about and count, which often includes many more than those that pass traffic (and also ignores/doesn't count some that do pass traffic).

•    Link data may provide references for reputation management or tracking of viral campaigns - again, items that analytics don't entirely encompass.

•    Competitive link data may be of critical importance to many marketers - this information can't be tracked any other way.

I admit it. SEOmoz is a search engine scraper - we do it for our free public tools, for our internal research and we've even considered doing it for clients (though I'm seriously concerned about charging for data that's obtained outside TOS). Many hundreds of large firms in the search space (including a few that are 10-20X our size) do it, too. Why? Because search engine APIs aren't accurate.

Let's look at each engine's abilities and data sources individually. Since we've got a few hundred thousand points of data (if not more) on each, we're in a good position to make calls about how these systems are working.

Google (all APIs listed here):

•    Search SOAP API - provides ranking results that are massively different from almost every datacenter. The information is often less than useless, it's actually harmful, since you'll get a false sense of what's happening with your positions.

•    AJAX Search API - This is really designed to be integrated with your website, and the results can be of good quality for that purpose, but it really doesn't serve the job of providing good stats reporting.

•    AdSense & AdWords APIs - In all honesty, we haven't played around with these, but the fact that neither will report the correct order of the ads, nor will they show more than 8 ads at a time tells me that if a marketer needed this type of data, the APIs wouldn't work.

Yahoo! (APIs listed here):

•    Search API - Provides ranking information that is a somewhat accurate map to Yahoo!'s actual rankings, but is occassionally so far off-base that they're not reliable. Our data points show a lot more congruity with Yahoo!'s than Google's, but not nearly enough when compared with scraped results to be valuable to marketers and businesses.

•    Site Explorer API - Shows excellent information as far as number of pages indexed on a site and the link data that Yahoo! knows about. We've been comparing this information with that from scraped Yahoo! search results (for queries like linkdomain: and site:) and those at the Site Explorer page and find that there's very little quality difference in the results returned, though the best estimate numbers can still be found through a last page search of results.

•    Search Marketing API - I haven't played with this one at all, so I'd love to hear comments from those who have.

MSN:

•    Doesn't mind scraping as long as you use the RSS results. We do, we love them and we commend MSN for giving them out - bravo! They've also got a web search SDK program, but we've yet to give it a whirl. The only problem is the MSN estimates, which are so far off as to be useless. The links themselves, though, are useful.

Ask.com

•    Though it's somewhat hidden, the XML.Teoma.com page allows for scraping of results and Ask doesn't seem to mind, though they haven't explicitly said anything. Again, bravo! - the results look solid, accurate and match up against the Ask.com queries. Now, if Ask would only provide links

I know a lot of you are probably asking:

•    "Rand, if scraping is working, why do you care about the search engines fixing the APIs?"

•    The straight answer is that scraping hurts the search engines, hurts their users and isn't the most practical way to get the data. Let me give you some examples:

•    Scraped queries have to look as much like real users as possible to avoid detection and banning - thus, they affect the query data that search engineers use to improve web search.

•    These queries also hit advertisers - falsifying the number of "real" impressions that advertisers see and lowering their CTRs unnaturally.

•    They take up search engine resources and though even the heaviest scraping barely impacts their server loads, it's still an annoyance.

•    With all these negative elements, and so many positive incentives to have the data, it's clear what's needed - a way for marketers/businesses to get the data they need without hurting the search engines. Here's how they can do it:

•    Provide the search ranking position of a site in the referral string - this works for ranking data, but not for link data and since Yahoo! (and Google) both send referrals through re-directs at times, it wouldn't be a hard piece to add.

•    Make the API's accurate, complete and unlimited

•    If the last option is too ambitious, the search engines could charge for API queries - anyone who needs the data would be more than happy to pay for it. This might help with quality control, too.

•    For link data - serve up accurate, wholistic data in programs like Google Sitemaps and Yahoo! Search Submit (or even, Google Analytics). Obviously, you'd only get information about your own site after verifying.

I've talked to lots of people at the search engine level about making changes this week (including Jeremy, Priyank, Matt, Adam, Aaron, Brett and more). I can only hope for the best...

Source: http://moz.com/blog/the-nasty-problem-with-scraping-results-from-the-engines