April 17, 2013
Held in Oslo, Norway, this year’s Enterprise Social and Search with SharePoint seminar promises its usual diverse audience and tech-based discussions. It will take place on May 14, 2013 from 9:00-11:30. Although official events begin at 9:00, show up early for breakfast and networking at 8:30.
The seminar is free, unless, of course you do not show up without providing advanced notice.
According to the seminars registration page, the audience will include the following:
“CIOs, IT Directors, Collaboration Leads, SharePoint Leads, Social Networking Leads, Enterprise Search Leads, Big Data Leads, Business Intelligence Leads, Communication Directors, HR Directors.”
Not a bad line up for a free seminar in Oslo. However, those who register but do not attend (and do not provide notice) will be charged a fee of kr. 200, or about $30 US dollars. Considering the expenses Comperio will shell out for each attendee, this no-show charge is an interesting approach to guaranteeing attendance and accounting for wasted expenses.
Samantha Plappert, April 17, 2013
April 11, 2013
Google is the reigning king of search, but some say that may be changing. After all-time highs in March, Google stock has slipped in early April. Chris Crum, in his article, “Will Google Ever Stop Dominating Search?” addresses some of the reasons for the subtle decline.
“Forbes, for example, has a piece out today called ‘Four Reasons Google’s Stock Is Slowing Down.’ The first two reasons listed in this article are directly related to this issue: 1. Losing search market share and 2. Shift to mobile search. The author references a New York Times article making the rounds today, in which the case is made that people, particularly on mobile, are choosing other services first, based on the type of information they’re looking for.”
Some predict that a combination of smaller specialized services will eventually take Google’s place, particularly on mobile. And while Google is not going anywhere anytime soon, it is a sign that the landscape of search is changing. One of the areas where a specialized service makes sense is enterprise search. A solution like LucidWorks is much better suited to the subtleties of the enterprise than a generic mega-solution like Google Analytics or SharePoint.
Emily Rae Aldridge, April 11, 2013
April 8, 2013
Elasticsearch is trying to expand its reach by partnering with other trendy tech services. It is definitely getting some headlines. The most recent headline is detailed by Market Watch in their article, “Fog Creek Selects Elasticsearch to Search and Analyze Terabytes of Data.”
“Elasticsearch, the company behind the popular real-time search and analytics open source project, today announced that Fog Creek has selected Elasticsearch to provide instant search capabilities within Kiln, its software development product. Kiln is designed to support and simplify development workflow for users searching more than 100,000 source code repositories. Elasticsearch is now a critical ingredient of Kiln, providing instant search for 300,000,000 requests across 40 billion lines of code to improve overall performance, reliability and user experience.”
Elasticsearch is known for collaboration with leading edge products, but it is not without its controversies as well. GitHub recently reached out to Elasticsearch to develop its new search infrastructure, but the service quickly exposed security concerns and then crashed. So when it comes to a search infrastructure that goes beyond trends, trust an industry standard. Do not assume that every search application will be safe enough for the enterprise. For instance, consider LucidWorks. They are built on open source Lucene/Solr, employ one quarter of the Core Committers on that project, and are optimized for the enterprise. Choose industry confidence, not trends.
Emily Rae Aldridge, April 8, 2013
April 8, 2013
Apache Solr has already claimed the role of one of the most popular and sought after search applications currently on the market. The Apache Solr platform uses Lucene to power its indexing and querying abilities. The Eventbrite article “Solr Unleashed SC” which was translated using Google translator gives details about the upcoming Solr Unleashed training class on June 13, 2013 in Brazil.
“Solr Unleashed is a complete training, hands-on, facing the Solr 4, or SolrCloud. The SolrCloud is a complete change of structure of Solr to facilitate installations of Big Data. Allows indexing distributed beyond search distributed, eliminating the need for master-slave configuration.”
The course will be spread out over two 8-hour days. Students will need to bring their own computer and will get the chance to develop a complete application. This application will actually be a real search prototype and students will learn it so that it can potentially be used for future projects. In addition students will also get an official certification of LucidWorks and will be given a digital copy of all the course material. The actual material will be in English but the course will be taught in Portuguese. Semantix, a LucidWorks partner company, will be giving the class. During the class students will not only get an in depth introduction to Solr but they will also get an up close and personal look at the new open source search system Solr 4. It’s great to see Solr growing and transcending to other languages. Looks like regardless of the language, search is where it’s at.
April Holmes, April 08, 2013
April 7, 2013
Now here is an interesting implication of social-graph analysis in business. The MIT Technology Review reports, “Social Networks Reveal Structure (And Weaknesses) of Business.” We’ve known for some time that, through the analysis of connections, social networks can reveal even more about us than is obvious to most users. Now, researchers at Israel’s Ben Gurion University used this concept to derive an impressive amount of information about businesses. The article reveals that the team begins:
“. . . by using a search engine to find the Facebook pages of a number of individuals who work for a specific company.
“Using these individuals as seeds, they then begin crawling the social networks, sometimes jumping from one network to another, looking for other individuals at the same company. These in turn become seeds to find more employees and so on.
“They end up with a basic network of links between employees within the company. It’s then that the fun begins.
“Using standard measures of connectedness, Fire and co then identified people in positions of leadership and by adding in details such as location, mined from the Facebook pages, they reconstructed the international structure of these organisations. They also used community detection algorithms to reconstruct the organisational structure of the company.”
Wow. The researchers used their method on several “well known hi-tech companies” and found startling details. For example, they found a cluster of comparatively disconnected folks at a large organization, and discerned they belonged to an acquired startup that had yet to be well-integrated into the company. This sort of information can be used by companies to monitor themselves, but it could also be used by potential investors (for good or ill for the business, I suppose, depending on what turned up.)
More ominously, competitors could use the information to their advantage. Now that this technology is in the news, many companies will want to prevent such details from emerging, but how? Researcher Michael Fire advises them to “enforce strict policies which control the use of social media by their employees.” Immediately, I might add. And, I suspect that whatever was previously considered a “strict policy” must become even more strict in order to avoid exposure from this technique.
Won’t employees be thrilled?
Cynthia Murrell, April 07, 2013
April 6, 2013
One of my two or three readers sent me a link to a LinkedIn post in the Information Access and Search Professionals section of the job hunting and consultant networking service. LinkedIn owns Slideshare (a hosting service for those who are comfortable communicating with presentations) and Pulse (an information aggregation service which plays the role of a selective dissemination of information service via a jazzy interface).
The posting which the reader wanted me to read was “How Natural Language Processing Will Change E Commerce Search Forever.” Now that is a bold statement. Most of the search systems we have tested feature facets, prediction, personalization, hit boosting for specials and deals, and near real time inventory updating.
The company posting the information put a version of the LinkedIn information on the Web at Inbenta.
The point of the information is to suggest that Inbenta can deliver more functionality which is backed by what is called “search to buy conversions.” In today’s economy, that’s catnip to many ecommerce site owners who—I presume—use Endeca, Exalead, SLI, and EasyAsk, among others.
I am okay with a vendor like Inbenta or any of the analytics hustlers asserting that one type of cheese is better than another. In France alone, there are more than 200 varieties and each has a “best”. When it comes to search, there is no easy way to do a tasting unless I can get my hands on the fungible Chevrotin.
Search, like cheese, has to be experienced, not talked about. A happy nibble to Alpes gourmet at http://www.alpesgourmet.com/fromage-savoie-vercors/1008.php
In the case of this Inbenta demonstration, I am enjoined to look at two sets of results from a the Grainger.com site. The problem is I cannot read the screenshots. I am not able to determine if the present Grainer.com site is the one used for the “before” and “after” examples.
Next I am asked to look at queries from PCMall.com. Again, I could not read the screenshots. The write up says:
Again, the actual details of the search results are not important; just pay attention that both are very different. But in both cases, wasn’t what we searched basically the same thing? Why are the results so different?
The same approach was used to demonstrate that Amazon’s ecommerce search is doing some interesting things. Amazon is working on search at this time, and I think the company realizes that its system for ecommerce and for the hosted service leaves something out of the cookie recipe.
My view is that if a vendor wants to call attention to differences, perhaps these simple guidelines would eliminate the confusion and frustration I experience when I try to figure out what is going on, what is good and bad, and how the outputs differ:
First, provide a link to each of the systems so I can run the queries and look at the results myself. I did not buy into the Watson Jeopardy promotion because in television, magic takes place in some editing studios. Screenshots which I cannot read nor replicate open the door to similar suspicions.
Second, to communicate the “fix” I need more than an empty data table. A list of options does not help me. We continue to struggle with systems which describe a “to be” future yet cannot deliver a “here and now” result. I have a long and winding call with an analytics vendor in Nashville, Tennessee which follows a similar, abstract path in explaining what the company’s technology does. If one cannot show functionality, I don’t have time to listen to science fiction.
Third, the listing of high profile sites is useful for search engine optimization, but not for making crystal clear the whys and wherefores of a content processing system. Specific information is needed, please.
To wrap up, let me quote from the Inbenta essay:
By applying these techniques on e-commerce website search, we have accomplished the following results in the first few weeks.
- Increase in conversion ratio: +1.73%
- Increase average purchase value: +11%
Okay, interesting numbers. What is the factual foundation of them? What method was used to calculate the deltas? What was the historical base of the specific sites in the sample?
In a world in which vendors and their pet consultants jump forward with predictions, assertions, and announcements of breakthroughs—some simple facts can be quite helpful. I am okay with self promotion but when asking me to see comparisons, I have to be able to run the queries myself. Without that important step, I am skeptical just as I was with the sci-fi fancies of the folks who put marketing before substance.
Stephen E Arnold, April 6, 2013
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April 6, 2013
Some welcome enhancements to MongoDB are included in the open-source data base’s latest release, we learn from “MongoDB 2.4 Can Now Search Text,” posted at the H Open. The ability to search text indexes has been one of the most requested features, and the indexing supports 14 languages (or no language at all.) The write-up supplies this handy link to a discussion of techniques for creating and searching text indexes.
The post describes a second feature of MongoDB 2.4, the hashed index and sharding:
“Hash-based sharding allows data and CPU load to be spread well between distributed database nodes in a simple to implement way. The developers recommend it for cases of randomly accessed documents or unpredictable access patterns. New Geospatial indexes with support for GeoJSON and spherical geometry allow for 2dsphere indexing; this, in turn, offers better spherical queries and can store points, lines and polygons.”
There is also a new modular authentication system, though its availability is limited so far. The project has also: added support for fixed sized arrays in documents; optimized counting performance in the execution engine; and added a working set size analyzer. See the article for more details, or see the release notes, which include upgrade instructions. The newest version can be downloaded here.
Cynthia Murrell, April 06, 2013
April 5, 2013
LinkedIn wants to make search easier for its members. The Computerworld article “LinkedIn Sharpens Search Engine Feature” gives all of the details about the new revamped search system. With this new system LinkedIn wants its members to be able to find information easier on their site. LinkedIn’s initial goal was to provide a place for professionals to place their career bios as well as interact with their peers and colleagues. However, LinkedIn has grown and now serves a much larger audience. Companies as well as various groups have set up pages. In addition there is a job section as well as a section where individuals and publishers can share or posts comments, as well as provide links to articles. LinkedIn’s search engine sales 5.7 billion queries last year alone so the new search features will definitely reach a large audience. Johnathan Podemsky, a LinkedIn product manager shared the following
“Now, all you need to do is type what you’re looking for into the search box and you’ll see a comprehensive page of results that pulls content from all across LinkedIn including people, jobs, groups and companies.”
In addition to segmenting their results users will also enjoy auto-complete and suggested search capabilities to help them fine-tune their query terms. The search engine will also keep a log of members search queries in order to help deliver better results. It is important to note that these changes will only be applied to the main site and not the mobile application. Regardless, these new search features will definitely improve LinkedIn search capabilities for users. It seems that LinkedIn is definitely paying attention to the needs of their users and takes search very serious. Users want good results but they also want a user friendly and efficient search system. Looks like LinkedIn is on the right page.
April Holmes, April 05, 2013
April 4, 2013
This morning I read “As Web Search Goes Mobile, Competitors Chip at Google’s Lead.” Keep in mind that when the link goes dead you will need the paper edition of the story on pages A 1 and A 4 of the April 4, 2013 issue or a for fee password to the New York Times’s online service.)
The main point is that mobile is surging. For many reasons, mobile search does not work the way desktop search and Web surfing worked when Backrub was bubbling toward Google. The article identifies the geolocation trend where coordinates coupled with some data about user behavior can deliver a place to buy coffee.
The article then says:
No longer do consumers want to search the Web like the index of a book — finding links at which a particular keyword appears. They expect new kinds of customized search, like that on topical sites such as Yelp, TripAdvisor or Amazon, which are chipping away at Google’s hold. Google and its competitors are trying to develop the knowledge and comprehension to answer specific queries, not just point users in the right direction.
The story then points out that there are 30 trillion Web address which is definitely quite a few places to index content. Searching a massive index with 2.5 words just does not work for “consumers.”
The story identifies social systems which put a person closer to someone or some information from someone which answers the user’s question. The wrap up to the article quotes a Google “fellow” who correctly states a Google truism:
“Most people have this very strong Google habit,” he said. “I go there every day and it gives me information I want, so it’s a self-reinforcing cycle. Not anyone can come in and just do those things.”
So what exactly is happening in consumer search? Outfits like Amazon and LinkedIn look like they are growing and presumably taking traffic from Google. On the other hand, Google seems confident that its market share and its remarkable diversity of ways to present information to users is in pretty good shape. Is this a chess-type draw, a paradox, or an analysis which makes search almost impossible to discuss without getting lost in clicks, segments, traffic, and user behavior data?
My view is that search has become a word which is acceptable in some circles and the equivalent of a curse word in others. Consumer wants answers to questions, and according to some experts, answers to questions the user does not know she yet has formulated. Vendors want revenue. Advertisers want people to buy their products and services. Teens want whatever teens want. Each tiny grouping of online users which can be labeled has search needs.
The problem is that figuring out exactly what the “need” is in a specific context is a field where further research and innovation are needed.
April 4, 2013
For companies tackling big problems related to large sets of data, Grant Ingersoll has the solution – search. At the recent GigaOm Structure: Data Conference, Ingersoll, CTO of LucidWorks, recommends that organizations take another look at search solutions. GigaOm covers the details in their story, “How Search Can Solve Big Data Problems.”
The article begins:
“There are many solutions for figuring out how to parse large amounts of data, but LucidWorks CTO Grant Ingersoll has a suggestion: use search. At GigaOM’s Structure:Data conference in New York City Thursday, Ingersoll laid out his case for why search is a big part of dealing with databases and indexes. ‘Search should be a critical part of your architecture,’ he told attendees. It is a system building block for any large problem you’re trying to solve that requires a ranked set of results. And it doesn’t have to be just text search, it can be for any type of search, he said.”
Ingersoll goes on to assert that search has changed dramatically quickly. For those organizations that have not updated their search solution in several years, there are more options on the market that are likely to serve their purposes more effectively. LucidWorks, Ingersoll’s company, is a longstanding name in the field, and yet has undergone dramatic changes even in the last few years. If your organization is exploring options for more effective search and Big Data management, LucidWorks is worth a serious look.
Emily Rae Aldridge, April 4, 2013