Semantic Search for Academic Social Networks
August 9, 2013
Arnetminer is an interesting service from China that we came across recently and feel compelled to share it. It is a tool that offers search and mining capabilities for academic and researcher social networks. Semantic technology is the name of its game.
There are several groups and organizations that have funded this service: Chinese Young Faculty Research Funding, IBM China Research Lab and Minnesota/China Collaborative Research Program among others. It was originally developed by Jie Tang in 2006.
We learned about the focal points of the system:
In this system, we focus on: (1) creating a semantic-based profile for each researcher by extracting information from the distributed Web; (2) integrating academic data (e.g., the bibliographic data and the researcher profiles) from multiple sources; (3) accurately searching the heterogeneous network; (4) analyzing and discovering interesting patterns from the built researcher social network.
It looks like the Introduction page was last updated in 2010, but the search engine itself seems to be going strong into 2013. In the past, the folks at Arnetminer have given talks at Google, the World Wide Web Conference and more. It would be interesting to know where they are currently making their rounds at.
Megan Feil, August 09, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Natural Language Interface Transforms Search
August 8, 2013
Projections and opportunities are often forecasted for emerging technologies and natural language processing is no exception. We took a look back at an article from earlier in the year posted on Semantic Web: “Looking Ahead to a User Experience Transformed by Conversational Interfaces and NLP.” According to this article, software that is able to understand human intention will play a vital role in transforming business processes and search technology.
IBM distinguished engineer Currie Boyle is quoted as stating the following:
This ecosystem change is happening in the industry…discussing the desire for business dialogue management systems to try to determine the intent of a user seeking information and the intent of the author who wrote it, and matching the two by that intent, even if they don’t share the same words in common to express it. The applications range from consumer conversational and context-aware systems to business professionals finding answers in structured or unstructured data through via natural language interfaces to boosting call contact center performance with dialogue management.
Expert System solutions offer precise analytics using their core semantic search technologies. Their linguistic analysis capabilities enhance the extraction and application of data in the natural language interface.
Megan Feil, August 8, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Sentiment Analysis in Search Bolsters Collaboration and More
August 1, 2013
We are seeing a lot of information published in regards to the ties between search and collaboration. As collaboration inherently relies on search, it is no wonder that these two are consistently discussed in tandem — “How Search Amplifies Enterprise Collaboration” from Business2Community points this out too.
This article discusses how social features and metadata make information more findable and thus more likely to be used in collaborative projects between users.
The author, Christian Buckley, explains his evolving perspective on sentiment analysis:
I questioned the ability of this technology to adequately interpret and intelligently map end user sentiment to content and metadata, or “data about data,” improving the overall search experience. Sentiment analysis is an incredibly difficult thing to automate, much less deliver within mainstream platforms. Thankfully, we have a method for providing a robust sentiment-based layer to our structured collaboration platforms: social collaboration. Even the search leaders recognize that they cannot completely replace human interaction (at least not yet) as the ultimate semantic classification mechanism.
Collaboration is one key reason companies are seeking out enterprise search vendors utilizing semantic technologies. Expert System is one such company whose solutions offer precise analytics using their core semantic search technologies. Their linguistic analysis capabilities enhance the extraction and application of data in the natural language interface. Collaboration is only the beginning, Expert System also has semantically enriched tools for social media monitoring, customer service and more.
Megan Feil, August 1, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Natural Language Interface Will Boost Mobile Enterprise Search
July 30, 2013
Enterprise organizations are increasingly loosening the leash on mobility and this is causing an emphasis on cross-device search. CMS Wire ran an article on the subject called, “Cross-Device Search: The Next Step in Mobile Search Delivery.” The author discusses the known issues with mobile search within the consumer sector and points to natural search interfaces as a remarkable technology that will be one of the building blocks of mobile search.
Both collaborative search and cross-device search stick out as technologies that many companies will begin needing to utilize more and more frequently.
The article does a good job summing up where mobile search delivery will begin:
In 2011 Greg Nudelman wrote Designing Search — UX Strategies for eCommerce Success which had a strong mobile focus and there is an excellent chapter on mobile search in the recent book on Designing the Search Experience by Tony Russell-Rose and Tyler Tate. There is a consensus that natural search interfaces will be an important feature of mobile search design.
Natural search interfaces, or natural language interface (as others call this technology), are a vital piece of technology delivered by many innovative companies like Expert System. One of their solutions, Cogito Answers, utilizes natural language interface to understand the intention of users to deliver information and answers quickly and accurately with a single click.
Megan Feil, July 30, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
The Developer Side of the Efficiency and Security Conversation
July 25, 2013
The ongoing conversation about efficiency in the enterprise can trace roots to several departments. It is a ubiquitous issue that every department has a vested interest in. A recent article, “Enhancing Enterprise Efficiency with IT Operations and Analytics,” discusses addressing productivity and efficiency from the perspective of IT.
The article describes a recent independent review that explained how Tulsa’s Information Technology Department had numerous inefficiencies. These bottlenecks ultimately prevented their department from providing acceptable service.
The article referenced above expounds on the issues mentioned in the review on Tulsa’s IT department:
The department is tasked with overseeing all electronic and communication systems for the municipal government, as well as managing its computing, mobile software and networking needs. Officials discovered that the 141-member agency had been woefully underfunded, inhibiting employees’ ability to monitor important tasks and properly identify potential issues. According to the news outlet, some of the software systems being deployed by the government included a 30-year-old police and courts record management system.
It takes collaboration between the business side and IT and developers to select, implement and deploy the right solution for any particular organization. Developers have the insight into nuanced semantic features in analytics solutions currently on the market; that knowledge is necessary for knowing if the expected use cases will pan out as expected. One solution we have been keeping tabs on is Cogito API, which offers government, intelligence, and corporate security clients oversight by extracting intelligence from data.
Megan Feil, July 25, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Business Efficiency to Increase with Semantic Search
July 23, 2013
Looking for an alternative to Google and other big-name web search platforms? Teach Amazing recommends “Hakia—Semantic Search Portal.” Writer Mark Brumley explains that the semantic web search portal presents multiple types of content in the same results page. The various sections encompass the gamut and this type of aggregated search displayed on a single point of access seems to be the wave of the future.
Brumley shares his user experience:
I love how search results are displayed. Various sections are populated on a single page. Sections include web, news, blogs, Twitter, images and videos. The Twitter feed is a real plus for me and gives an indication of the current pulse of a particular topic. Give Hakia a try the next time you are doing some research. Make sure you try it in the classroom as well. Students need to know that Google is not the only search provider on the planet.
Brumley is not alone in recognizing the advantages of parsing data with context and meaning that semantic search provides. The enterprise also functions more efficiently when using tools that take a semantic approach to data. For example, Expert System offers solutions that empowers users to work at new heights of discovery and collaboration.
Megan Feil, July 23, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search.
Semantic Search Strengthened with Innovative Linguistic Analysis
July 16, 2013
In Search Engine Journal we came across a recent article outlining two important topics in the search arena today, “The Difference Between Semantic Search and Semantic Web.” The post presents definitions for each and delves into the numerous distinctions between these terms.
Pulling from Cambridge Semantics, the article asserts that the Semantic Web is a set of technologies that store and query information, usually numbers and dates. Textual data is not typically stored in large quantities.
We thought their simple explanation of semantic search was a good starting point for those learning about the technology:
Semantic Search is the process of typing something into a search engine and getting more results than just those that feature the exact keyword you typed into the search box. Semantic search will take into account the context and meaning of your search terms. It’s about understanding the assumptions that the searcher is making when typing in that search query.
We also appreciate that the article refers to semantic search as a concept that is not new, but is currently gaining much traction. Essentially semantic search mirrors the process people use when reading; text is analyzed and context is developed in order for a rich understanding to be developed. Many innovative technologies are emerging out of this concept. For example, solutions from Expert System offer precise analytics using their core semantic search technologies. Their linguistic analysis capabilities enhance the extraction and application of data in the natural language interface.
Megan Feil, July 16, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search
Bitext Delivers a Breakthrough in Localized Sentiment Analysis
May 29, 2013
Identifying user sentiment has become one of the most powerful analytic tools provided by text processing companies, and Bitext’s integrative software approach is making sentiment analysis available to companies seeking to capitalize on its benefits while avoiding burdensome implementation costs. A few years ago, Lexalytics merged with Infonics. Since that time, Lexalytics has been marketing aggressively to position the company as one of the leaders in sentiment analysis. Exalead also offered sentiment analysis functionality several years ago. I recall a demonstration which generated a report about a restaurant which provided information about how those writing reviews of a restaurant expressed their satisfaction.
Today vendors of enterprise search systems have added “sentiment analysis” as one of the features of their systems. The phrase “sentiment analysis” usually appears cheek-by-jowl with “customer relationship management,” “predictive analytics,” and “business intelligence.” My view is that the early text analysis vendors such as Trec participants in the early 2000’s recognized that key word indexing was not useful for certain types of information retrieval tasks. Go back and look at the suggestions for the benefit of sentiment functions within natural language processing, and you will see that the idea is a good one but it has taken a decade or more to become a buzzword. (See for example, Y. Wilks and M. Stevenson, “The Grammar of Sense: Using Part-of-Speech Tags as a First Step in Semantic Disambiguation, Journal of Natural Language Engineering,1998, Number 4, pages 135–144.)
One of the hurdles to sentiment analysis has been the need to add yet another complex function which has a significant computational cost to existing systems. In an uncertain economic environment, additional expenses are looked at with scrutiny. Not surprisingly, organizations which understand the value of sentiment analysis and want to be in step with the data implications of the shift to mobile devices want a solution which works well and is affordable.
Fortunately Bitext has stepped forward with a semantic analysis program that focuses on complementing and enriching systems, rather than replacing them. This is bad news for some of the traditional text analysis vendors and for enterprise search vendors whose programs often require a complete overhaul or replacement of existing enterprise applications.
I recently saw a demonstration of Bitext’s local sentiment system that highlights some of the integrative features of the application. The demonstration walked me through an online service which delivered an opinion and sentiment snap in, together with topic categorization. The “snap in” or cloud based approach eliminates much of the resource burden imposed by other companies’ approaches, and this information can be easily integrated with any local app or review site.
The Bitext system, however, goes beyond what I call basic sentiment. The company’s approach processes contents from user generated reviews as well as more traditional data such as information in a CRM solution or a database of agent notes, as they do with the Salesforce marketing cloud. One important step forward for Bitext’s system is its inclusion of trends analysis. Another is its “local sentiment” function, coupled with categorization. Local sentiment means that when I am in a city looking for a restaurant, I can display the locations and consumers’ assessments of nearby dining establishments. While a standard review consists of 10 or 20 lines of texts and an overall star scoring, Bitext can add to that precisely which topics are touched in the review and with associated sentiments. For a simple review like, “the food was excellent but the service was not that good”, Bitext will return two topics and two valuations: food, positive +3; service, negative -1).
A tap displays a detailed list of opinions, positive and negative. This list is automatically generated on the fly. The Bitext addition includes a “local sentiment score” for each restaurant identified on the map. The screenshot below shows how location-based data and publicly accessible reviews are presented.
Bitext’s system can be used to provide deep insight into consumer opinions and developing trends over a range of consumer activities. The system can aggregate ratings and complex opinions on shopping experiences, events, restaurants, or any other local issue. Bitext’s system can enrich reviews from such sources as Yelp, TripAdvisor, Epinions, and others in a multilingual environment
Bitext boasts social media savvy. The system can process content from Twitter, Google+ Local, FourSquare, Bing Maps, and Yahoo! Local, among others, and easily integrates with any of these applications.
The system can also rate products, customer service representatives, and other organizational concerns. Data processed by the Bitext system includes enterprise data sources, such as contact center transcripts or customer surveys, as well as web content.
In my view, the Bitext approach goes well beyond the three stars or two dollar signs approach of some systems. Bitext can evaluate topics or “aspects”. The system can generate opinions for each topic or facet in the content stream. Furthermore, Bitext’s use of natural language provides qualitative information and insight about each topic revealing a more accurate understanding of specific consumer needs that purely quantitative rating systems lacks. Unlike other systems I have reviewed, Bitext presents an easy to understand and easy to use way to get a sense of what users really have to say, and in multiple languages, not just English!
For those interested in analytics, the Bitext system can identify trending “places” and topics with a click.
Stephen E Arnold, May 29, 2013
Sponsored by Augmentext
Temis and MarkLogic Collaborate on Big Data Challenges
April 18, 2013
Well, this is quite a surprise. Temis announces, “TEMIS and MarkLogic Strengthen Strategic Alliance.” Semantic content-management firm Temis is partnering with MarkLogic, who boasts of providing the only enterprise NoSQL database in the market, to tackle unstructured data. The press release tells us:
“With new, enhanced integration capabilities, TEMIS’ Luxid® and MarkLogic® Server can now help organizations do more with their content. . . .
“TEMIS’ Luxid® and MarkLogic® Server count many joint customer implementations. Their integration delivers seamless semantic enrichment of data stored in the enterprise NoSQL database with the Luxid® domain-specific and multilingual annotation process. This enables organizations to build powerful Big Data applications, combining content semantics with real-time database agility to make massive volumes of unstructured content easier to exploit.”
Metadata master Temis was Founded in 2000 by some folks with IBM-based text-mining experience under their belts. The company now has offices across Europe and North America. This year, their flagship Luxid Content Enrichment Platform won the Software & Information Industry Association‘sCodie Award for Best Semantic Technology Platform.
With a laser focus on efficient and fruitful databases, MarkLogic is headquartered in Silicon Valley, with offices around the world. The company was founded in 2001, and has been working beyond the relational database since long before “big data” became a buzzword.
Cynthia Murrell, April 18, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Temis and MarkLogic: Timid? Not on the Semantic Highway
April 12, 2013
My in box overfloweth. Temis has rolled out a number of announcements in the last 10 days. The company is one of the many firms offering “semantic” technology. Due to the vagaries of language, Temis is in the “content enrichment” business. The idea is that technology indexes key words and concepts even though a concept may not be expressed in a text document. I call this indexing, but “enrichment” is certainly okay.
The first announcement which caught my attention was a news release I saw on the Marketwatch for fee distribution service. The title of the article was “TEMIS Completes Successful Wide Scale Semantic Content Enrichment Test in Windows Azure.” A news release about a test struck me as unusual. The key point for me was that Temis is positioning itself to go after the SharePoint add in market.
The second announcement was a news story distributed by Eureka Alert called “Wiley Selects Temis for Semantic Big Data Initiative The key point is that a traditional publishing company has licensed software to do what humans used to do in a venerable publishing company which, until recently, was sticking with traditional methods and products. Will Temis propel John Wiley to the top of the leader board of professional publishers? Hopefully some information will become available quickly.
The third announcement which I noted was “Temis and MarkLogic Strengthen Strategic Alliance.” The write up hits the concepts of semantics and big data. Here’s the passage which intrigued me:
MarkLogic® Server is the only enterprise NoSQL database designed for building reliable, scalable and secure search, analytics and information applications quickly and easily. The platform includes tools for fast application development, powerful analytics and visualization widgets for greater insight, and the ability to create user-defined functions for fast and flexible analysis of huge volumes of data.
I am uncomfortable with the notion of “only”. MarkLogic is an XML centric data management system. Software wrappers can use the XML back end for a range of applications. These include something as exotic as a Web site for the US Army to more sophisticated applications for publishing technical documents for an aircraft manufacturing firm. However, there are a number of ways to accomplish these tasks and some of the options make use of somewhat similar technology; for example, eXist-db. While not perfect, the fact that an alternative exists only increases my discomfort with an “only”.
So what’s up? My hunch is that both MarkLogic and Temis are in flat out marketing mode. Clusters of announcements are, in my experience, an indication that the pipeline needs to be filled. Equally surprising is that MarkLogic into a big data player and an enterprise search system, not a publishing system. Most vendors are morphing. The tie up with Temis suggests that Temis’ back end needs some beefing up. The MarkLogic positioning is that it is now a player in semantics and big data. I think that partnering is a quick way to fill gaps.
Will MarkLogic blast through the $100 million in revenue ceiling? Will Temis emerge as a giant slayer in semantic big data? The company recently raised $25 million to become a player in big data. (See “Big Data Boon: MarkLogic Pulls In $25 Million In VC Funding”.) Converting $25 million into high margin revenue could tax the likes of Jack Welch in his prime.
My hunch is that both firms’ management teams have this as a 2013 goal. With the patience of investors wearing thin for many search and content processing vendors, closed deals are a must. The economy may be improving for analysts on CNBC, but for search vendors, making Autonomy-scale or Endeca-scale revenues may be difficult, if not impossible.
In my opinion, the labels “big data” and semantics do not by themselves deliver revenue the way Google delivers Adwords. As more search firms chase additional funding, has the world of search switched from finding information for customers to getting money to stay in business?
No timidity visible as these two firms race down the semantic interstate.
Stephen E Arnold, April 12, 2013
-
- Subscribe to Beyond Search
Feature archive
News archive
-
