Law enforcement needs on-the-job text analytics to tackle massive data analysis challenge

Imagine trying to extract useful information from 50,000 lines of chat logs? Now, imagine if that needle in a haystack was the difference between a criminal being caught or going free?

Thousands of lines of confusing and unreadable chat text are increasingly becoming part of police investigations, in addition to the wealth of digital evidence associated with the many types of investigations conducted every day. Not to mention the trove of documents that officers potentially store on personal and shared drives within their agencies.

Law enforcement agencies around the world today face real challenges in providing effective policing services as they struggle to cope with the volume, velocity and increasing complexity of the data they collect and generate.

Their employees, who use traditional, manual, iterative processes often carried out by multiple people across the organization, face a real challenge in making critical real-time connections to threat, risk and harm.

Failure to make these connections misses opportunities to protect the most vulnerable and opportunities to intervene and intervene with high-risk offenders. It can also damage public confidence in the police.

Manually extracting all available information from the collection of material officers requires additional human resources, taking officers away from front-line duties.

Empowering researchers with text analytics

Traditional analytical techniques are not enough in this new world of data-driven policing. But, using the latest advances in text analytics combined with natural language processing, they can begin to extract intelligence from existing data. It facilitates the analysis of structured and unstructured data together in one place, ensuring that everything found is presented in an investigative context.

This technique allows the researcher to clearly identify where the greatest risk and harm is, while also identifying the most vulnerable and ensuring that all opportunities to intervene and engage high-risk offenders are used in real time.

Using this technique, they quickly:

• find more By accessing and analyzing large amounts of data, including large volumes of unstructured data.
• More disruptionConnecting more automatically, quickly and intelligently, finding the most vulnerable people and those who pose the greatest risk to them.
• Avoid moreBy combining a better and more timely understanding of what is happening with better tactical and strategic assessments and better public engagement, legal and policy development.
• Get involved and support moreTargeting resources and support to those most at risk and in greatest need.
• Improve your partnershipBy building trust and confidence and protecting and using data shared by partners to greater effect.
• Work more efficientlyContinuous improvement of triage and prioritization through artificial intelligence. Improved ability to connect the dots across a geographically distributed investigative workload reduces waste and duplication, increases workforce efficiency, and frees up personnel to focus on other pressing investigative and intelligence duties.

In doing so, they ‘move a needle in a haystack’ and ensure that more crime is thwarted and that everything that can be done is done to protect the most vulnerable people in our society.

Learn more about how advanced technologies like text analytics are being used in public safety and criminal justice