Archive for the ‘Support’ Category

Contacting Lexalytics support services

Thursday, November 1st, 2012

In addition to contacting Lexalytics support services via email at support@lexalytics.com, we have now opened a new channel for contacting us using the Lexalytics support portal at support.lexalytics.com.

This blog article will cover using the support portal to create, edit/update, close, and manage tickets.

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Support Notes: Windows runtime prerequisites

Monday, October 22nd, 2012

In many cases, the runtime support needed for Salience Engine deployments on Windows systems exists on the target systems. However, there are times that installation on a clean Windows system requires the appropriate Visual C++ runtime support. The Windows installers are built to attempt to download and invoke the Visual C++ runtime installs. But there are environments in which, for one reason or another, that download from Microsoft’s site of the Visual C++ runtime fails. In these situations, it’s recommended that the runtime support be downloaded and installed manually through the URLs provided in this article.

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Multi-language support in Salience

Friday, October 12th, 2012

At Lexalytics, we know it’s not only a global marketplace, but a multi-lingual global marketplace. It’s this understanding which has driven us to extend the capabilities of Salience beyond analysis of only English content. This article details the evolution and current state of our support for performing text analytics on English and non-English content.

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Support Notes: Apache configuration support

Tuesday, October 2nd, 2012

At times, problems may be encountered when setting up Apache to host PHP pages containing Salience PHP wrapper method call which includes a “HTTP/1.0 500 Internal Server Error” when visiting the PHP page and a corresponding /var/log/httpd/error_log “PHP Fatal error: Call to undefined function…” error message entry.

Figure 1: Visiting PHP page with Salience PHP method calls locally hosted by Apache

Figure 2

Figure 2: 1st error—HTTP/1.0 500 Internal Server Error

Figure 3

Figure 3: 2nd error—"PHP Fatal error: Call to undefined function…" in error_log

This is even after verifying the dynamic extension to the saliencefive.so has been added in the php.ini configuration file loaded by Apache.

Under this circumstance, it is observed that the start, stop, or restart of Apache daemon produces the warning message, “httpd: Could not reliably determine the server’s fully qualified domain name, using 127.0.0.1 for ServerName”

Figure 4: httpd start/stop/restart warning

This warning indicates that httpd (Apache daemon) was unable to determine its own name and it may raise no concern since the message informs that Apache would automatically assign a domain name. However, the server needs to know its own name under certain circumstances in order to generate self-referential redirects. This is the main cause for the PHP page hosting problems.

To eliminate the errors, add a fully-qualified ServerName defined in the main httpd configuration file (typically located in /etc/httpd/conf/).

Examples:
SeverName localhost
ServerName 127.0.0.1
ServerName 10.201.2.99 (substitute for actual server IP address)

Figure 5: Adding ServerName entry to httpd.conf

Figure 6: Successfully reaching PHP page

Sizing your Salience Five deployment

Thursday, December 22nd, 2011

This is another extract from our customer files. Not something that comes up all the time, but often enough that it warranted a blog article with a good worked example.

In general, Salience Engine has been and continues to be very economical in terms of hardware requirements. Text analytics with Salience Engine is more CPU intensive than I/O or memory intensive, though the inclusion of the Concept Matrix™ in Salience Five has increased the memory footprint.

So let’s say you’re looking to process 2 million documents per day, where half are tweets and half are news articles of 4kb or less. What kind of hardware spec are you looking at? Read on to see how you could spec out handling this amount of content with Salience Five.

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Entity extraction in Salience Five

Wednesday, December 21st, 2011

I wanted to write up a detailed explanation of the methods of entity extraction available in Salience Five for a client, where they overlap and where they differ. And as I did, I thought, “That would make for a bloody useful blog post for the dev blog.” So here it is.

Prior to Salience 4.x, entity extraction was solely list-based. Salience 4.0 introduced model-based entity extraction, which allowed for novel entity extraction. In other words, “I didn’t think to add ‘John Smith’ to my list of people to extract, but Salience Engine found him in today’s news magically because it knows what names of people look like.” Very powerful stuff.

Salience Five continues to provide model-based and list-based entity extraction found in Salience 4.x, with some of the same cross-over between the two and modification to the terminology.

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Ten things to know about Salience (part 2)

Friday, April 22nd, 2011

This is a follow-on to our list of ten things to know about Salience Engine. Together, these two articles are intended to guide developers in some of the main aspects of working with Salience Engine when they first start out.

In the first part, most of the topics focused on deployment strategies and approaches. In this second part, we’ll look at areas of tuning results from Salience Engine. So let’s roll up our shirt-sleeves and get back into it…

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Ten things to know about Salience (part 1)

Friday, April 22nd, 2011

I had a meeting with a client recently, and one of the suggestions they raised was a list of the top 10 things that an engineer should know when they start working with Salience Engine. Some of these may seem basic, however it’s not safe to assume that things which seem obvious actually are. With all due respect to David Letterman and his Late Night Top Ten lists, here we go…

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Getting started with Salience Engine in python

Wednesday, April 6th, 2011

One of the key strengths with Salience Engine is that it is provided as a library, which customers can integrate into their own systems. In order to make the integration easier, we provide wrappers for some of the most popular development environments; namely .NET, Java, PHP, and python. The first hurdle for a developer to cross in accessing Salience Engine is getting the wrapper of choice set up within their development environment so they can start coding against it. This blog article shows how to build and deploy the python wrapper for Salience Engine on both Windows and Linux. Also provided is an interactive script written by one of our professional services engineers that can also be used to get your feet with Salience Engine in a python environment.

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Short term fix for sentiment memory leak

Thursday, February 10th, 2011

One of the benefits of producing software for developers is that you get to work with some really smart folks as customers. And sometimes, they bring issues to our attention that we’ve missed. Such is the case with a small memory leak that was brought to our attention by DataSift recently. They are one of the few customers that work with our C API, so they’ve gotten familiar with Salience Engine at the lowest level we expose. We worked with Ben at DataSift to characterize the leak and develop a workaround pending a fix in a future release of Salience Engine. This article details the leak that was discovered and the interim workaround. A permanent fix will be included in our next update of Salience 4.4.

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