Natural Language Processing (NLP) 1 June 2019 Anat Bielsky Previous Article Next Article What is Natural Language Processing? Understanding human language is a complex subject, since we express ourselves in various ways both orally and in writing. There are hundreds of languages, each with its own syntax, grammar, slang, etc. Furthermore, when writing, we tend to use abbreviating and drop punctuation. Other challenges we might face when analyzing speech include regional accents, mumbling, and terms acquired from other languages. Natural Language Processing is a branch of Artificial Intelligence that assists computers in understanding, analyzing and interpreting human Language. This branch allows computers to communicate with humans in their own language and assess unstructured data related to language. For example, NLP enables computers to read text, hear speech, interpret it, assess emotion and define which parts of the text is more important. What types of data can be analyzed and reviewed? Structured data - data organized in orderly format. For example, data in SQL tables with columns and rows. They feature a relation index and can be easily charted. Semi-structured data - data which isn't stored in a structured database yet features some organizational properties that simplify the analysis. A certain processing can arrange them in a certain context. For example, XML data. Unstructured data - data which is not organized in a predefined manner or is not stored in a predefined database, from texts excerpted from medical records to texts published on social media channels. Nowadays, computers analyze more language-based data than humans, considering the vast amount of unstructured data generated on a daily basis. Automation is critical for text and speech data analysis. What is NLP used for? NLP technology plays a great role in Artificial intelligence applications, some of which implement machine learning combined with NLP for risk analysis, customer behavior review, Chatbots and fraud detection. One of the most common uses of NLP is aimed at the various search apps, both audio and textual (for further details, click here ). The search engine uses NLP to analyze the query and retrieve the most relevant answers. Users used to have to search by keywords. Nowadays, you can simply state complex sentences that then serve as the basis for your search. When searching by voice, the search questions are said, then recorded and processed by an interface which converts speech into text while filtering background noises, then analyzed for the different phonemes, adapted to words then finally converted to a sentence which becomes query. This query is sent to the system, which in turn sends the appropriate answer. In an age in which people can speak to Siri and Alexa as freely as they speak to one another, many people can benefit greatly from these apps. These abilities can be used for other applications, too. For example, Facebook uses a tool titled DeepText to analyze posts published on the social network. DeepText is a text analysis engine that can detect positive and negative emotions expressed in written posts, automatically tag and retrieve themes from texts. The objective is to reach insights/conclusions from a text and in some cases even convert it to actual action. An example of this implementation is Chatbots response to a spoken question). Google has its own NLP tools, including: API Natural Language Cloud- this tool enables exposing the structure and meaning of the text. It allows retrieving information on people, locations and events to understand the information transferred through social media and client conversations. This tool allows classifying files by 700 predefined categories. AutoML Natural Language- a machine learning NLP-oriented tool which enables creating personally adapted models for organizations to categorize, retrieve, and detect different elements in a text. Here’s how it works: The user loads the various data into the computer (the more varied the examples, the more accurate the process) Runs the module adapted to their needs Assesses the received results. In case the received insights are insufficiently precise, update the module, then review the results again. Source: https://cloud.google.com/natural-language/#how-automl-natural-language-works NLP and Knowledge Management Both AI tools (such as Natural Language Processing) and Knowledge Management tools center around treating knowledge and information as a central component. Both are essentially intertwined. Without reliable knowledge and initial charting of the required templates, the machines would not be able to elaborate, create or implement knowledge optimally. Furthermore, the field of KM has generated the strategic processes that allow organizations to make the knowledge created with their automatic tools optimally accessible to all relevant parties. References: Natural Language Processing (NLP) Natural Language AI curatti

Converting a content community 1 October 2012 Sagit Salmon Previous Article Next Article Every organization transitioning to a new system must convert its content from the old system to the new, regardless of the way decisions are made regarding prioritizing the converted content and how said content is selected. Assuming we've indeed decided to convert a certain community, some actions are best to be taken before and during the conversion process. Converting a community is an excellent chance to recharacterize its content tree and structure and refresh its content. Do not settle for simply transferring the current structure as is. This decision might lead to missing out on many advantages the new system offers that might suit the community and its users. Even if your review leads to retaining the current settings, this is a long-term investment that is certainly worthwhile. First, we must define which themes from the current community will be included in the new community and accordingly define its content tree (which subjects will it include and the hierarchy between them) and write a requirements’ analysis document. After defining which subjects the new community requires, deal with the content itself. This task requires another filtering process, deciding which content passes through and which does not. If possible, delete the redundant content at this stage, preventing a possible scenario in which it is transferred to the new community due to lack of attention or time. Old content usually remains undealt with in the future; the theoretical day on which you will find the time to delete old content never comes. At this point, it is recommended to review the possible conversion methods, automatic conversion's advantage of speed versus manual conversion's quality. Conversion methods can be combined according to the existing content (not all content can or should be automatically converted; not every manual conversion provides added value). In any case, this stage must be performed as the content's integrity must be reviewed. I highly recommend creating a content mapping document besides the document that contains detailed content regarding the pages and windows on the current community and note where each page/window will appear in the new community and in what form as well as its appropriate conversion method. If possible, refer to the amount of content in each window. This document usually serves the entire project crew and helps us better assess the time the conversion process requires and enables a close watch on progress ensuring we don't forget any content. Setting up a community can take place after the requirements’ analysis document is completed along the conversion document. Content should be entered only after the community setup is complete. Entering content should be performed workers who do not have another job; employing these workers is cost effective. However, to ensure the process is carried out as planned, someone must be allocated to supervise the process, directing and monitoring content enterers' performance. We thus recommended both a conversion document and deleting old content at an early stage. Content editors will do just that; they will not alter website structure, add missing windows or ponder upon the content's validity. Whatever content stored on the old website can be transferred as is to its required location on the new website; if an infrastructure does not exist, content feeders are to proceed (yet notify the monitor). Remember the better the infrastructure and preparation, the simpler and quicker the content entering. Once the content is entered to the new community, each update must be doubled and will as such take double the time. In conclusion, community conversion includes steps similar to those taken when setting up a new community yet involve a different focus. When setting up a new community we must focus on characterization; when converting a community we must focus on content.

How did Big Data become the raw material of the new world? 1 March 2023 Lior Cohen Previous Article Next Article Collecting huge volumes of data, AKA Big Data, has changed the way we live and work. The rise of Big Data has led to significant changes in the way we make decisions, solve problems and interact with each other. Today, big data is everywhere and has become a major force shaping the world's future. How did we improve by using Big data? Currently, decisions and changes in various areas of our lives are made based on the massive collection of data and by machine learning that analyzes it and converts it from a flood of information into intelligence. This can be demonstrated by various examples: Science and Research – Scientists and researchers can now analyze massive amounts of data to uncover patterns that were previously undetectable. This analysis led to major breakthroughs in fields such as genetics, environmental science, archeology, and more. Medicine and Health - Big Data enables personalized medicine and adapting the treatment to each patient's needs, identifying potential risks, and preventing disease. Economy - Big Data enables a deep review and analysis of the economy, with important insights on prices, trends, fluctuations in the capital market, and business activity. This allows businesses to adapt their financial decisions to the current economic situation and to prepare for different situations. Transportation - A vast variety of information on transportation is collected using Big Data. This includes data on vehicle traffic, public transportation, different activities in the public space, and more. This data allows users to manage their time and plan trips in advance and for engineers to develop smarter and more efficient solutions for those using the road. Big data also enables a more efficient and safer technological analysis of future transportation, such as electric and autonomous vehicles, which will make their way while communicating with other vehicles around them and with traffic lights while also detecting obstacles. Advertising and Marketing - With the proliferation of social media and other online platforms, Big Data has a significant impact on society as a whole. We generate enormous amounts of information about our lives, preferences, and behaviors. This data is used by companies and organizations to characterize advertising campaigns and other marketing efforts. All in all, Big Data affects many of the important aspects of our lives, allowing us to adapt our activities to the current reality and to carry out more efficient planning. How can Big Data help us in the organization? Big data helps organizations make data-based decisions and understand various processes and trends, identify new opportunities, and act accordingly. The data includes information about customer needs, financial data, sales information, product history, and more. All this allows organization management to make data-based decisions much more quickly and accurately than in the past. Technology allows organizations to adapt to the changing needs of the market, plan business strategies and achieve new goals. This also contributes to the optimization of internal processes - the data allows organizations to understand which processes are undergoing distortion or inefficiency and decide on ways to improve them. So, we're basically redundant here, aren't we? In a world overloaded with data, the human element plays a major role (at least for now). Managing data efficiently calls for key human qualities: Ask the right questions - the vast amount of information available today probably contains all the information we need and more. If in the past wisdom entailed locating knowledge or demonstrating knowledge, today we are required to fish it out of the immense ocean of information. The queries we will run through the search engine, and the conversation box used for conversing with Chat GPT, our filtering process will apply to the reports we will run, which will allow technology to fulfill our dream. Differentiate between different levels of importance - filtering out background noise is part of success. Our world is full of background noise, an endless stream of information from every direction. Alerts pop up non-stop, and the competition for our attention becomes more and more intense in every possible way, both in the physical space and in the virtual space, in every possible form - audio, video, text... We will have to choose what to consume and from what to generate insights. Distinguish between truth and lies - the world of big data creates a freedom of information unprecedented in human history, which leads to a variety of opinions, interpretations and even outright lies that are presented as established facts. The human eye is the one that will be forced to determine what to accept and what to reject. What does the future have in store? Looking ahead, the impact of big data is expected only to grow. As more and more devices connect to the Internet, we will create even more data than we do today. This will create new opportunities for innovation and growth but will also raise new challenges related to privacy, security, and ethical issues. Luckily, there are enough people to help us out.

Let them develop Applications for SharePoint 2013! 1 December 2015 Elad Piran Previous Article Next Article The 2013 version of SharePoint is characterized, among other things, by its Apps architecture- not only are its Web Parts available for use on the website, so are the App Parts which are 'building blocks' structured for setting up the website and as such have their designated uses. Furthermore, the organization can purchase more apps via the Microsoft Application Shop using a model derived from the successful mobile application model. Nevertheless, there might be a specific organizational need which is not addressed by the existing apps, including those available at the shop. This situation calls for application development. Application development for SharePoint 2013 Application development for SharePoint 2013 is simple. The various development tools grow more sophisticated with each version and simplify the development process. In the past, developing code X was applicable exclusively on website X. In order to use the application on another website, one had to conduct some adjustments to the site. These apps, however, are "closed" building blocks, available for use on any website we wish. All you have to do is distribute and utilize. Thus, one app development can serve many organization workers who now do not need to turn to the developer- they can simply search for the relevant app in the organization's app collection. This is Re-Use at its best. Note: Microsoft has lately decided to change the term SharePoint Apps to the new term SharePoint Add-ins. Click here for a detailed explanation on the Microsoft website. Hereby are some instruction videos (from YouTube) for getting started with app development in a SharePoint environment: Introduction to SharePoint 2013 App Model Developing Apps for SharePoint 2013 with Visual Studio 2013 Developing Apps for SharePoint 2013 with Visual Studio 2012 Of course, there are thousands of other available video manuals of this sort. Do you want to leverage this option in your organization? Announce a contest between the organization's development workers involving innovation and entrepreneurship in the field of SharePoint 2013 application development. Provide them with time and incentive and who knows? Maybe one of them will develop the next hot solution for your organization. Your developers will need ideas for what kind of application is needed. Well, announce a contest between all SharePoint users in the organization, in which the users offer innovative ideas for development. These ideas can then be suggested to your application developers!

To our Chinese colleagues- Join a lecture "ISO 30401 in a strategic business view" on the July 28th Previous Item Next Item To our Chinese colleagues: On July 28th, Dr. Moria Levy, in collaboration with MentoringCo, will be giving a lecture titled "ISO 30401 in a strategic business view." The session will be conducted in English with Chinese translation. For more details, please contact: moria@kmrom.com .

Professional Knowledge Development Previous Service Next Serice Developing professional knowledge by aggregating existing documented and tacit assets, and using it to construct new knowledge levels. ROM offers a unique solution for the development of professional knowledge whose products include a model, bodies of knowledge, and accompanying tools. This process has been used in hundreds of projects and was proven to promote our customers' professional capabilities.

So how can a maturity model based on ISO standard 30401 help organizations? 1 December 2021 Dr. Moria Levy Previous Article Next Article KMGN ISO30401 team. December the 2nd, 2021. Today we meet- 8 people representing seven countries, all keen to make a difference. We discuss enablers that can help knowledge managers who are hesitating whether and how to start implementing ISO standard 30401. When talking about assessments that may be part of an implementation toolbox, the question of a maturity model pops. ISO itself never has maturity models (not like CMMI standards). Certification of ISO standards is like a light switch. It's turned on (having been certified) or off (otherwise). Maturity models are more similar to dimmer; they include several levels. But a maturity model does have its advantages and can be easily designed even in an ISO environment, and is important as it can leverage ISO30401 usage. Developing such includes building an assessment for every standard chapter (the knowledge management system, leadership, planning, support, operation, and improvement). Each assessment can contain parameters, based on sub-clauses and keywords mentioned in the specific chapter, these being reviewed and graded in 5 levels, from poor to high. One can evaluate the organization regarding these topics in the KM context. The direct benefit is a set of grades representing a gap analysis to a potential ISO30401 certification. The indirect and much more important result is having a compass based on ISO30401, as on how the organization can improve its KM initiatives and hence, its business results. This maturity model was not yet developed; however, I believe it will not be long before we invest our resources in such. Be patient. Or even better- help us in doing so. This post was initially published in LinkedIn

Zen and the art of Knowledge Management 1 December 2010 Previous Article Next Article The following short piece, in its personal tone, is slightly different than what you've probably read in our magazine so far. My name is Tali and I am a senior Knowledge Management consultant and have been working at ROM for the last three and a half years. During these full and interesting years I have learned the fascinating methodology of Knowledge Management became acquainted with the world that underlies this doctrine and have managed many Knowledge Management projects for large organizations. In recent years, I have also delved into a process of both studying and practicing the way of Zen Buddhism, a path that offers one to explore and discover their own consciousness, feelings and thoughts and reach balance and tranquility through meditative sitting. I used the word "also" since I really did view these two aspects of my life as parallel; how could Knowledge Management and Zen Buddhism meet? I can invest in both worlds and progress in their respective paths but they don't seem to have anything in common. Only recently have I realized that they actually have a lot in common and that the joy I derive from both fields is rooted in the same internal essence. The inner search engine Only one who searches, can understand the person who has yet to find. No one tries to reveal their self if they don't sense their self is concealed from them- if they haven't experienced those days they find themselves surprisingly managed by thoughts, fears or a sudden wave of emotions of an unknown source. This discontentment and emotional overflow leads people to begin searching. This is true not only on an individual/spiritual level but on an organizational level as well; if everything is clear and accessible even in turbulent times (organizational crises) since the knowledge, data and information are retrievable and processed in a manner that clearly and sharply serves the organizational decision making- there is no need to begin searching. Organizations usually turn to us when they experience discontentment, when knowledge created on one side of the organization doesn't find its way to the other side of the organization; when chasing after knowledge and information becomes a matter of routine; when the wheel is repeatedly reinvented and there is no synchronization, synergy and especially no harmony. The search for a clear and quiet place that enables us to use the organizational intellect or the individual power of thought, is the same mechanism that aspires to make decisions from a knowing, clear and serene place. The way to grow It is no coincidence that meditative thought involves crossing one's legs and a straight back. The wide, grounded and stable base provided by the crossed legs allow the back and head to grow upwards. This resembles one of the Buddhistic tradition's most initial and sacred symbols, symbolizing the spiritual path every person must walk on throughout their life; it is composed of one's large and wide left foot that is the base for the ladder that leads one upwards. This means that without grounding, without a large and wide basis, without roots the tree cannot grow towards the sky. Like the individual path, so does the organizational learning and growing process require a base. We have often been requested by organization to arrive and manage learning, innovation or lesson learning meetings yet these meetings became a platform for people to meet each other, exchange knowledge on projects in the organization and exchange basic information to which they did not have access previously. We tend to describe the process thus: "from knowledge holding, to knowledge sharing, to knowledge management". In other words, the organizational knowledge exists in people' brains, in documents, on computers, in islands in the organizations. Our initial goal is to build bridges and tunnels and make sure that the knowledge is flowing throughout the organization and that it is being shared between the different units and ranks and that the knowledge base is wide and shared. Every individual's creative essence, which evolves and grows, can be revealed and made accessible to said individuals only after they attain balance- not the emotion nor the brain vibrant and in control; not anger, or sadness and not even the great emotional experiences. Only through balance and serenity can a direction be suddenly found, and creativity/prosperity realized. This is also true regarding Knowledge Management: only when the knowledge is transferred from the organization's endowed parts to its weaker areas and have created a uniform level of knowledge, only through this serenity can the existing, available and accessible lead to learning, growth and evolution. Only this base can lead to new ideas, learning that leads organizational and personal development and to the development of new and innovative knowledge. The big hive Thousands of years this was all clear to us all; it's stated in every religion and ancient tradition: we are all one. The universe is one. The page on which I am writing encompasses the sun that warmed the trees, the water that nourished them ,the woodsman and his family, the paper company workers, the pen manufacturers and me, the person writing on this paper. This idea faded over the years. We've become individualists, private secluded beings. However, the processes this last century has seen have brought us back to our unified self: globalization, the world wide web and the blurred borders between organizations are all bringing back the feeling that we are all living in one big hive. We are all one entity in many ways. This is the direction knowledge management and sharing in organizations if heading towards. The knowledge is perceived as an organizational asset that isn't appropriated by a specific person or group of people, rather accumulated and converted into an 'organizational intellect' which is a whole that is greater than the sum of its parts. Transferring the knowledge and sharing between the different parts of the organization create this hive-like structure that functions in harmony. This image makes it easier to understand how a 'jam' in the knowledge flow can affect the entire organization and interfere with its functioning. On ROI and Nirvana One thing that always stood out in these two paths I've chosen to walk on, Knowledge Management and spirituality, is the need to invest over time, nurture over time and be ever so patient. In Knowledge Management, like meditative sitting, it is very hard to prove a ROI in such short time. It is a process in which your consciousness changes gradually and something becomes quieter, more creative and ultimately happier. This is also true for Knowledge Management: an organizational change, a change of sharing culture, beyond the "knowledge is power" approach to an approach that views sharing and Knowledge Management prominently. We must practice, work and believe. What about Nirvana? We will reach enlightenment when we do not regress , when we don't need to ask or be asked "why are we even doing this?". The day the serene, meditative and connected outlook will be the perspective through which I view my entire life. The day Knowledge Management will be so embedded in the work processes, so present and supportive of every area of organizational life, adding value to all aspects. On that day we won't need to push or even want; it will simply be there.

Redefining Knowledge Management: Adding an Emotional Component to the Formal Definition 1 October 2022 Dr. Moria Levy Previous Article Next Article For many years the KM society held an interesting debate about the definition of knowledge management. In the first decade, people didn't really agree on its scope, some including only knowledge-in-our-heads, others also adding documented knowledge as part of what this discipline deals with. The next decade focused on how to turn our shared understanding of knowledge management into one sentence that holds it all. I remember a post titled "47 definitions of knowledge management and still counting". Study books included a series of possible definitions. They were all proper, each highlighting another perspective of KM. In 2018, ISO30401 was published, including a concise definition: "management with regard to knowledge." This new definition was very accurate; however, it hardly added clarity. Two notes were added to this definition, yet the fog remained. A few months ago, we published an amendment to 30401, including new and improved definitions. KM was redefined as: "Holistic, cross-functional discipline and set of practices, focused on knowledge, that improve organizational performance Note: Knowledge management includes, but is not limited to, the creation, acquisition, application, maintenance, sharing, and protection of knowledge to create organizational value." So now we could sleep better. A shared definition exists, published by a formal and respectful institute, and not too many will argue about its accuracy or clarity. Well... not exactly. It was all in it- but the soul. Reading this definition, one could understand, but less sense KM. And that is where I want to come up with a suggestion: Let's keep this formal definition. It is required, and having one source is essential. However, let us add an alternative, non-formal definition of KM, adding the emotional component into this equation. I suggest a first draft of this alternative definition: "knowledge management is understanding the importance of knowledge as a main asset and key to success, therefore handling it wisely, with care and tender." Additional ideas are more than welcome. This post was initially published in LinkedIn

Responsive or mobile: which website is preferable? 1 June 2017 Yael Peichich Previous Article Next Article In this day and age, we all understand that any internet website, should also be adapted to small screens of all sorts (cellular/tablets/laptops/etc.) Although many “experts” erroneously consider responsive websites and websites optimized for mobile content, there is actually a vast difference between the two. A mobile-optimized website is a website which presents content from the “main” website optimized for mobile users’ needs, mainly those that lead to an activity. This content usually includes only vital information such as contacts and a telephone number. This website is totally separate from the “main” website which is usually connected to a common management system yet was constructed by another code which was planned, characterized and designed differently and uniquely. A responsive website, more accurately known as a responsive design website, adapts itself automatically to the size of the screen through which it is being viewed while retaining the website’s full content and configuration as it appears when accessed via computer. In other words, the user does not realize the “surfing” environment has changed. Both types of websites are meant to generate a quality experience for mobile users which in turn motivates quick action. So, if you’ve decided to build a website suitable for various mobile devices and are debating whether to design it responsively or to optimize its content for mobile, here are a few pointers that should be considered: The type of data displayed on the website: when a user is searching for a local business (restaurant/garage/first aid/etc) he/she is actually searching for a telephone number to call or an address to reach. It is redundant to display a website filled with pages which simply do not provide any added value at this certain point in time. However, if said user is seeking a service provider (e.g. a business consultant) he/she will search for extensive relevant information on the website, such as recommendations. Financial concern: A responsive website uses a common code for all platforms. Any modification to the website is performed only once. A mobile website is a separate entity and as such uses a separate code than the main website. Therefore, any update must be performed twice (which in turn means double maintenance). Advertising spaces: It is far more difficult to control advertising spaces when dealing with a responsive website, while a mobile site displays banners in a fixed location, size and form. Cellular services: Some services cannot be fully utilized in cellular devices when setting up a responsive website, such as location services (e.g. finding the closest garage to user’s whereabouts), direct connection to navigation application (such as Waze or Google Maps) or the Click to Call feature which allows the user to directly contact the business (without having to copy & paste the number). Tip: it is preferable to review the data from Google Analytics in order to reach the correct decision regarding the message you wish the website to convey. For example, if you are operating a responsive website with a dropout percentage higher than mobile entries, this is definitely a sign that a full optimization to mobile (it it possible that the buttons or phone number on the website are too small to click and force the user to magnify the display). Although important, differentiating between responsive and mobile websites does not turn deciding which is preferable easier. That said, the various considerations are now clearer- and that is a fine point from which to start.

Conferences Previous Item Next Item International Conference on Knowledge Management and Semantic Technology ICKMST April 12-13, 2023 Venice, Italy https://waset.org/knowledge-management-and-semantic-technology-conference-in-april-2023-in-venice American Productivity and Quality Center Conference (APQC) April 17-20, 2023 Houston, TX https://www.eventscribe.net/2023/apqcconf/aaStatic.asp?SFP=U1JMUUxWVUxAMTI2MTU 6th International Conference on Knowledge Management Systems (ICKMS 2023) May 10-12, 2023 Atlanta, GA http://ickms.org/ The Knowledge Management Education Hub June 28-Jul 1, 2023 Geneva, Switzerland https://kmeducationhub.de/knowledge-management-conference-km-conference/

Knowledge Engineering: AI and KM- the perfect marriage 1 July 2021 Dr. Moria Levy Previous Article Next Article KMGN: KM-AI course Session 17, July 27th. Today Art opens a window to the fabulous world of knowledge engineering. We are past the first stage of our AI project, and we already know what business challenge we are dealing with. Knowledge engineering is the process we carry to turn the business issue into data and algorithms that will operate on them. Note: Refer to the SECI model components of it. Step 1: Understand the baseline business process; understand the problems and challenges of this issue- syntax, semantic and perspective. Understand their root causes (Externalization). Step 2: Describe the model. Describe it in free format (Externalization) and then extract a structured description (Combination). Of course, automatic knowledge graph construction can serve well for this step. Be sure your taxonomy is in place. Step 3: Let the machine analyze the data and try learning from it (Combination). Step 4: Share the initial ideas and add Subject Matter Experts' input (Socialization). Step 5: Perform some sensemaking. Understand the findings (Externalization). Step 6: Return to both / either expert and machine, improving their understandings (Internalization). Perform the last steps again and again. Upon completion- celebrate success! This post was initially published in LinkedIn