Slow down, life sciences: why the industry’s not ready for consumer technologies in clinical settings

Frank Traina

Frank Traina

The life sciences industry is changing at a remarkable rate. While many companies specializing in pharmaceuticals, biotechnology, and medical products and devices have embraced consumer technologies, others stand uncertainly at the gate, weighing the price of entry. As my colleague Sameer noted, the opportunities are numerous, including improved patient care, lower TCO, greater productivity, and compliance with regulatory and consumer demands. But as many companies are learning the hard way, there are also significant barriers to adopting consumer technologies in clinical settings. Read more of this post

Luck be a lady—twice: behind the scenes at AT&T Developer Summit’s Hackathon

JD Jordan

JD Jordan

Mapping apps are great at getting first responders to a building.
But not into it. And not at winning.

For the second year in a row, I joined the Slalom Atlanta custom development team at the 2014 AT&T Developer Summit Hackaton. And for the second year in a row, we came in second place—always the bridesmaid…ahem, bridesgroom—with our finalist app, RescueRoute, beating out nearly 120 teams after only 24 hours of design and development. Read more of this post

State-of-the-art mobile search part 8: evaluation

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 7: Spelling Correction

Rod Smith

Rod Smith

This blog series presented search features for offline-capable mobile apps. Most aspects of the solutions were explained with multiple implementation options, e.g., the TF-IDF models, unigram vs. bigram language model, noisy channel edit model, indexing term positions and/or related terms, etc. To evaluate the fitness of any particular combination of the search implementation options for a particular mobile app, it helps to quantify the quality of the search results. Read more of this post

State-of-the-art mobile search part 7: spelling correction

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 6: Search Execution

Rod Smith

Rod Smith

Search query terms that are absent from the corpus may be treated as potentially misspelled words. A search engine can improve the search experience by identifying potentially misspelled query words through its inverted index and by proposing likely corrections through a metric called the edit distance and an n-gram language model. Read more of this post

State-of-the-art mobile search part 6: search execution

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 5: Term Canonicalization

Rod Smith

Rod Smith

As explained in prior installments in this series, advanced search relies on term frequency and inverse document frequency. Together, those two factors reflect the importance of a term in a given document with respect to the rest of the corpus, which tells the search engine how relevant a document is given a single search term.

To optimize search execution, term frequency and independent document frequency are calculated for each term and document in the corpus before executing search queries. Then, when a search query is issued, the search engine quickly scores each document for the given search terms. Read more of this post

One-cloud solution takes a media company to new heights

Art Fort

Art Fort

For the past year, I’ve been working with a media and entertainment client on a SaaS application. Hosted on Amazon Web Services (AWS), the application provides creative professionals with a “one-cloud” solution for media and content collection, collaboration, production, and transcoding of high-value, high-definition content.

I’ve been fortunate to be part of this project from the beginning—starting with some small proof of concepts, to doing a cloud migration assessment of their on-premise technologies, and ultimately contributing to application architecture, development, and deployment onto AWS. For me, two things set this project apart: the team and the technology. Read more of this post

Pro tips for making the most of IWNY with mobile

Internet Week New York (IWNY) is the largest Internet festival in the world. The event’s hub—IWNY HQ in Silicon Alley—will attract some 10,000 attendees between May 20 and 23.

It’s exciting to be in the tech hub of New York City at Internet Week, where tomorrow’s trends are being formed today. The successful start-ups in media and technology are shaping the way our clients will better connect with their customers, partners, and employees, and the tech-elite are all here during the festival to share their experiences.

Read more of this post

State-of-the-Art Mobile Search Part 5: Term Canonicalization

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 4: Fields and Phrases

Rod Smith

Rod Smith

The inverted index built in earlier parts of this series use an undefined function canonicalize(word) to convert strings of characters into a standard form. Doing so accounts for the fact that there are multiple forms of most words in English and similar languages. Consider a query like the following:

3d printing donuts”

Crude search engines match literal words of the search query against literal words from the document collection with case insensitive substring matching. Literal substring matching is obviously deficient given its failure to match the query above against documents that contain the following:

  • “3D Printers Make Donuts Healthy”
  • “… a 3D-printed donut….”
  • “Dunkin Donuts has made a 3D printer.”

To match the search query above with those documents, search engines can employ various types of term canonicalization that ignore non-semantic details like grammatical class, so printing matches print, printed, printers, etc.  The most common approach for English-language search is known as stemming.

Read more of this post

State-of-the-Art Mobile Search Part 4: Fields and Phrases

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 3: TF-IDF Models

Rod Smith

Rod Smith

The inverted index and the ranked retrieval model from earlier in this series did not distinguish between different fields of the indexed documents, nor did they make any special accommodation for multi-word phrases.

Phrase queries

A user may need to find documents that contain multi-word phrases like “all your base.” Users understand phrase queries well enough that explicit phrase queries are one of the few effective types of advanced queries. Typically, users identify phrase queries by enclosing each phrase in quotes, but implicit phrase queries are also possible, where a search engine identifies phrases without quotes or any other indication beyond the mere proximity of the words. Read more of this post

State-of-the-Art Mobile Search Part 3: TF-IDF Models

State-of-the-Art Mobile Search is a series exploring how to implement advanced mobile search.

State-of-the-Art Mobile Search Part 2: Ranked Retrieval

Rod Smith

Rod Smith

The ranked retrieval model explained in part 2 of this series established a framework for assessing the relevance of documents for a search query in terms of the information content of each query term and the focus of each document.

Term Frequency Models

If a search term t appears several times in one document d1 but fewer times in another document d2 of similar length, d1 is arguably more relevant to t than d2 is. However, if d1 has ten occurrences of t, while d2 has t just once, that does not make d1 ten times more relevant than d2. Read more of this post

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